Python A-Z™: Python For Data Science With Real Exercises!

  • Course provided by Udemy
  • Study type: Online
  • Starts: Anytime
  • Price: See latest price on Udemy
Udemy

Course Description

Learn Python Programming by doing!

There are lots of Python courses and lectures out there. However, Python has a very steep learning curve and students often get overwhelmed. This course is different!

This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward.

After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples.

This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises.

In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course!

I can't wait to see you in class,

Sincerely,

Kirill Eremenko

Who this course is for:

  • This course if for you if you want to learn how to program in Python
  • This course is for you if you are tired of Python courses that are too complicated
  • This course is for you if you want to learn Python by doing
  • This course is for you if you like exciting challenges
  • You WILL have homework in this course so you have to be prepared to work on it

Instructors

Data Scientist
  • 4.5 Instructor Rating
  • 502,545 Reviews
  • 1,843,224 Students
  • 45 Courses

My name is Kirill Eremenko and I am super-psyched that you are reading this!

Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes.

From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events.

To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!

Helping Data Scientists Succeed
  • 4.5 Instructor Rating
  • 510,085 Reviews
  • 1,809,544 Students
  • 119 Courses

Hi there,

We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more!

We are here to help you stay on the cutting edge of Data Science and Technology.

See you in class,

Sincerely,

The Real People at Ligency

Expected Outcomes

  1. Learn to program in Python at a good level Learn how to code in Jupiter Notebooks Learn the core principles of programming Learn how to create variables Learn about integer, float, logical, string and other types in Python Learn how to create a while() loop and a for() loop in Python Learn how to install packages in Python Understand the Law of Large Numbers Curated for the Udemy Business collection Course content 8 sections • 75 lectures • 11h 10m total length Expand all sections Welcome To The Course 6 lectures • 13min Installing Python (Windows & MAC) Preview 08:55 BONUS: Learning Paths 00:34 Get the materials 00:05 Some Additional Resources!! 00:13 FAQBot! 01:28 Your Shortcut To Becoming A Better Data Scientist! 02:05 Core Programming Principles 10 lectures • 1hr 14min Updates on Udemy Reviews 01:09 Types of variables 08:44 Using Variables 08:58 Boolean Variables and Operators 06:03 The "While" Loop 09:56 The "For" Loop 07:57 The "If" statement Preview 12:29 Code indentation in Python 02:40 Section recap 03:08 HOMEWORK: Law of Large Numbers 12:51 Core Programming Principles 5 questions Fundamentals Of Python 11 lectures • 1hr 18min What is a List? 03:15 Let's create some lists 08:42 Using the [] brackets 06:28 Slicing 09:27 Tuples in Python 06:17 Functions in Python 05:37 Packages in Python Preview 13:39 Numpy and Arrays in Python 07:08 Slicing Arrays 04:32 Section Recap 03:06 HOMEWORK: Financial Statement Analysis 10:11 Fundamentals of Python 5 questions Matrices 12 lectures • 1hr 59min Project Brief: Basketball Trends 08:16 Matrices Preview 03:31 Building Your First Matrix 16:50 Dictionaries in Python 14:20 Matrix Operations 08:34 Your first visualization 11:04 Expanded Visualization 09:37 Creating Your First Function 11:09 Advanced Function Design 11:15 Basketball Insights Preview 11:17 Section Recap 04:07 HOMEWORK: Basketball free throws 08:43 Matrices 5 questions Data Frames 12 lectures • 1hr 59min Importing data into Python Preview 08:25 Exploring your dataset 10:51 Renaming Columns of a Dataframe 02:56 Subsetting dataframes in Pandas 16:31 Basic operations with a Data Frame 09:49 Filtering a Data Frame 18:52 Using .at() and .iat() (advanced tutorial) 09:01 Introduction to Seaborn Preview 10:47 Visualizing With Seaborn: Part 1 10:05 Keyword Arguments in Python (advanced tutorial) 10:42 Section Recap 04:30 HOMEWORK: World Trends 06:57 Data Frames 5 questions Advanced Visualization 14 lectures • 2hr 36min What is a Category data type? 10:29 Working with JointPlots 07:38 Histograms 07:52 Stacked histograms in Python 18:29 Creating a KDE Plot 07:59 Working with Subplots() 14:05 Violinplots vs Boxplots Preview 08:55 Creating a Facet Grid 12:28 Coordinates and Diagonals 07:54 BONUS: Building Dashboards in Python 16:31 BONUS: Styling Tips Preview 15:46 BONUS: Finishing Touches 14:48 Section Recap 05:37 HOMEWORK: Movie Domestic % Gross 07:57 Advanced Visualization 5 questions Homework Solutions 9 lectures • 1hr 49min Homework Solution Section 2: Law Of Large Numbers 08:57 Homework Solution Section 3: Financial Statement Analysis (Part 1) 10:30 Homework Solution Section 3: Financial Statement Analysis (Part 2) 13:39 Homework Solution Section 4: Basketball Free Throws 17:23 Homework Solution Section 5: World Trends (Part 1) 15:45 Homework Solution Section 5: World Trends (Part 2) 14:35 Homework Solution Section 6: Movie Domestic % Gross (Part 1) 16:46 Homework Solution Section 6: Movie Domestic % Gross (Part 2) 08:19 THANK YOU bonus video 02:40 Bonus Lectures 1 lecture • 2min ***YOUR SPECIAL BONUS*** 02:02 Requirements No prior knowledge or experience needed. Only a passion to be successful! Description Learn Python Programming by doing! There are lots of Python courses and lectures out there. However, Python has a very steep learning curve and students often get overwhelmed. This course is different! This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward. After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples. This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises. In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course! I can't wait to see you in class, Sincerely, Kirill Eremenko Who this course is for: This course if for you if you want to learn how to program in Python This course is for you if you are tired of Python courses that are too complicated This course is for you if you want to learn Python by doing This course is for you if you like exciting challenges You WILL have homework in this course so you have to be prepared to work on it Show more Show less Featured review HIMANSHU SHEKHAR 4 courses 1 review Rating: 5.0 out of 5 a year ago The instructor have a really good way to explain everything and if you want to learn from scratch, you can go ahead with this course. Update after 50%: Kirrill is knowledgeable instructor and knows ways to make stuff easy to understand. Show more Show less Instructors Kirill Eremenko Data Scientist 4.5 Instructor Rating 502,545 Reviews 1,843,224 Students 45 Courses My name is Kirill Eremenko and I am super-psyched that you are reading this! Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes. From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events. To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you! Show more Show less Ligency Team Helping Data Scientists Succeed 4.5 Instructor Rating 510,085 Reviews 1,809,544 Students 119 Courses Hi there, We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more! We are here to help you stay on the cutting edge of Data Science and Technology. See you in class, Sincerely, The Real People at Ligency Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6776ed3acaf653eb',m:'33edd50905eea3a8908ed7bac1fbf8062b3ab11c-1627735558-1800-ASWJFGF00dis7WmX0/l8bYnTXZqDkjM1tWcZ/9HC0HmRme9hGGecosWqQo+J7Ff/go+tVjC9tLMFTSWNM10cg96xqCZrGuzNAWLTSUyPVCyDp65FCrVejovHtznACIs7+nXFLRt2IN/eMw+5pFGfwV4=',s:[0x982d9765f6,0xc8fb42d932],}})();
  2. Learn how to code in Jupiter Notebooks Learn the core principles of programming Learn how to create variables Learn about integer, float, logical, string and other types in Python Learn how to create a while() loop and a for() loop in Python Learn how to install packages in Python Understand the Law of Large Numbers Curated for the Udemy Business collection Course content 8 sections • 75 lectures • 11h 10m total length Expand all sections Welcome To The Course 6 lectures • 13min Installing Python (Windows & MAC) Preview 08:55 BONUS: Learning Paths 00:34 Get the materials 00:05 Some Additional Resources!! 00:13 FAQBot! 01:28 Your Shortcut To Becoming A Better Data Scientist! 02:05 Core Programming Principles 10 lectures • 1hr 14min Updates on Udemy Reviews 01:09 Types of variables 08:44 Using Variables 08:58 Boolean Variables and Operators 06:03 The "While" Loop 09:56 The "For" Loop 07:57 The "If" statement Preview 12:29 Code indentation in Python 02:40 Section recap 03:08 HOMEWORK: Law of Large Numbers 12:51 Core Programming Principles 5 questions Fundamentals Of Python 11 lectures • 1hr 18min What is a List? 03:15 Let's create some lists 08:42 Using the [] brackets 06:28 Slicing 09:27 Tuples in Python 06:17 Functions in Python 05:37 Packages in Python Preview 13:39 Numpy and Arrays in Python 07:08 Slicing Arrays 04:32 Section Recap 03:06 HOMEWORK: Financial Statement Analysis 10:11 Fundamentals of Python 5 questions Matrices 12 lectures • 1hr 59min Project Brief: Basketball Trends 08:16 Matrices Preview 03:31 Building Your First Matrix 16:50 Dictionaries in Python 14:20 Matrix Operations 08:34 Your first visualization 11:04 Expanded Visualization 09:37 Creating Your First Function 11:09 Advanced Function Design 11:15 Basketball Insights Preview 11:17 Section Recap 04:07 HOMEWORK: Basketball free throws 08:43 Matrices 5 questions Data Frames 12 lectures • 1hr 59min Importing data into Python Preview 08:25 Exploring your dataset 10:51 Renaming Columns of a Dataframe 02:56 Subsetting dataframes in Pandas 16:31 Basic operations with a Data Frame 09:49 Filtering a Data Frame 18:52 Using .at() and .iat() (advanced tutorial) 09:01 Introduction to Seaborn Preview 10:47 Visualizing With Seaborn: Part 1 10:05 Keyword Arguments in Python (advanced tutorial) 10:42 Section Recap 04:30 HOMEWORK: World Trends 06:57 Data Frames 5 questions Advanced Visualization 14 lectures • 2hr 36min What is a Category data type? 10:29 Working with JointPlots 07:38 Histograms 07:52 Stacked histograms in Python 18:29 Creating a KDE Plot 07:59 Working with Subplots() 14:05 Violinplots vs Boxplots Preview 08:55 Creating a Facet Grid 12:28 Coordinates and Diagonals 07:54 BONUS: Building Dashboards in Python 16:31 BONUS: Styling Tips Preview 15:46 BONUS: Finishing Touches 14:48 Section Recap 05:37 HOMEWORK: Movie Domestic % Gross 07:57 Advanced Visualization 5 questions Homework Solutions 9 lectures • 1hr 49min Homework Solution Section 2: Law Of Large Numbers 08:57 Homework Solution Section 3: Financial Statement Analysis (Part 1) 10:30 Homework Solution Section 3: Financial Statement Analysis (Part 2) 13:39 Homework Solution Section 4: Basketball Free Throws 17:23 Homework Solution Section 5: World Trends (Part 1) 15:45 Homework Solution Section 5: World Trends (Part 2) 14:35 Homework Solution Section 6: Movie Domestic % Gross (Part 1) 16:46 Homework Solution Section 6: Movie Domestic % Gross (Part 2) 08:19 THANK YOU bonus video 02:40 Bonus Lectures 1 lecture • 2min ***YOUR SPECIAL BONUS*** 02:02 Requirements No prior knowledge or experience needed. Only a passion to be successful! Description Learn Python Programming by doing! There are lots of Python courses and lectures out there. However, Python has a very steep learning curve and students often get overwhelmed. This course is different! This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward. After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples. This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises. In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course! I can't wait to see you in class, Sincerely, Kirill Eremenko Who this course is for: This course if for you if you want to learn how to program in Python This course is for you if you are tired of Python courses that are too complicated This course is for you if you want to learn Python by doing This course is for you if you like exciting challenges You WILL have homework in this course so you have to be prepared to work on it Show more Show less Featured review HIMANSHU SHEKHAR 4 courses 1 review Rating: 5.0 out of 5 a year ago The instructor have a really good way to explain everything and if you want to learn from scratch, you can go ahead with this course. Update after 50%: Kirrill is knowledgeable instructor and knows ways to make stuff easy to understand. Show more Show less Instructors Kirill Eremenko Data Scientist 4.5 Instructor Rating 502,545 Reviews 1,843,224 Students 45 Courses My name is Kirill Eremenko and I am super-psyched that you are reading this! Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes. From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events. To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you! Show more Show less Ligency Team Helping Data Scientists Succeed 4.5 Instructor Rating 510,085 Reviews 1,809,544 Students 119 Courses Hi there, We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more! We are here to help you stay on the cutting edge of Data Science and Technology. See you in class, Sincerely, The Real People at Ligency Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6776ed3acaf653eb',m:'33edd50905eea3a8908ed7bac1fbf8062b3ab11c-1627735558-1800-ASWJFGF00dis7WmX0/l8bYnTXZqDkjM1tWcZ/9HC0HmRme9hGGecosWqQo+J7Ff/go+tVjC9tLMFTSWNM10cg96xqCZrGuzNAWLTSUyPVCyDp65FCrVejovHtznACIs7+nXFLRt2IN/eMw+5pFGfwV4=',s:[0x982d9765f6,0xc8fb42d932],}})();
  3. Learn the core principles of programming Learn how to create variables Learn about integer, float, logical, string and other types in Python Learn how to create a while() loop and a for() loop in Python Learn how to install packages in Python Understand the Law of Large Numbers Curated for the Udemy Business collection Course content 8 sections • 75 lectures • 11h 10m total length Expand all sections Welcome To The Course 6 lectures • 13min Installing Python (Windows & MAC) Preview 08:55 BONUS: Learning Paths 00:34 Get the materials 00:05 Some Additional Resources!! 00:13 FAQBot! 01:28 Your Shortcut To Becoming A Better Data Scientist! 02:05 Core Programming Principles 10 lectures • 1hr 14min Updates on Udemy Reviews 01:09 Types of variables 08:44 Using Variables 08:58 Boolean Variables and Operators 06:03 The "While" Loop 09:56 The "For" Loop 07:57 The "If" statement Preview 12:29 Code indentation in Python 02:40 Section recap 03:08 HOMEWORK: Law of Large Numbers 12:51 Core Programming Principles 5 questions Fundamentals Of Python 11 lectures • 1hr 18min What is a List? 03:15 Let's create some lists 08:42 Using the [] brackets 06:28 Slicing 09:27 Tuples in Python 06:17 Functions in Python 05:37 Packages in Python Preview 13:39 Numpy and Arrays in Python 07:08 Slicing Arrays 04:32 Section Recap 03:06 HOMEWORK: Financial Statement Analysis 10:11 Fundamentals of Python 5 questions Matrices 12 lectures • 1hr 59min Project Brief: Basketball Trends 08:16 Matrices Preview 03:31 Building Your First Matrix 16:50 Dictionaries in Python 14:20 Matrix Operations 08:34 Your first visualization 11:04 Expanded Visualization 09:37 Creating Your First Function 11:09 Advanced Function Design 11:15 Basketball Insights Preview 11:17 Section Recap 04:07 HOMEWORK: Basketball free throws 08:43 Matrices 5 questions Data Frames 12 lectures • 1hr 59min Importing data into Python Preview 08:25 Exploring your dataset 10:51 Renaming Columns of a Dataframe 02:56 Subsetting dataframes in Pandas 16:31 Basic operations with a Data Frame 09:49 Filtering a Data Frame 18:52 Using .at() and .iat() (advanced tutorial) 09:01 Introduction to Seaborn Preview 10:47 Visualizing With Seaborn: Part 1 10:05 Keyword Arguments in Python (advanced tutorial) 10:42 Section Recap 04:30 HOMEWORK: World Trends 06:57 Data Frames 5 questions Advanced Visualization 14 lectures • 2hr 36min What is a Category data type? 10:29 Working with JointPlots 07:38 Histograms 07:52 Stacked histograms in Python 18:29 Creating a KDE Plot 07:59 Working with Subplots() 14:05 Violinplots vs Boxplots Preview 08:55 Creating a Facet Grid 12:28 Coordinates and Diagonals 07:54 BONUS: Building Dashboards in Python 16:31 BONUS: Styling Tips Preview 15:46 BONUS: Finishing Touches 14:48 Section Recap 05:37 HOMEWORK: Movie Domestic % Gross 07:57 Advanced Visualization 5 questions Homework Solutions 9 lectures • 1hr 49min Homework Solution Section 2: Law Of Large Numbers 08:57 Homework Solution Section 3: Financial Statement Analysis (Part 1) 10:30 Homework Solution Section 3: Financial Statement Analysis (Part 2) 13:39 Homework Solution Section 4: Basketball Free Throws 17:23 Homework Solution Section 5: World Trends (Part 1) 15:45 Homework Solution Section 5: World Trends (Part 2) 14:35 Homework Solution Section 6: Movie Domestic % Gross (Part 1) 16:46 Homework Solution Section 6: Movie Domestic % Gross (Part 2) 08:19 THANK YOU bonus video 02:40 Bonus Lectures 1 lecture • 2min ***YOUR SPECIAL BONUS*** 02:02 Requirements No prior knowledge or experience needed. Only a passion to be successful! Description Learn Python Programming by doing! There are lots of Python courses and lectures out there. However, Python has a very steep learning curve and students often get overwhelmed. This course is different! This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward. After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples. This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises. In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course! I can't wait to see you in class, Sincerely, Kirill Eremenko Who this course is for: This course if for you if you want to learn how to program in Python This course is for you if you are tired of Python courses that are too complicated This course is for you if you want to learn Python by doing This course is for you if you like exciting challenges You WILL have homework in this course so you have to be prepared to work on it Show more Show less Featured review HIMANSHU SHEKHAR 4 courses 1 review Rating: 5.0 out of 5 a year ago The instructor have a really good way to explain everything and if you want to learn from scratch, you can go ahead with this course. Update after 50%: Kirrill is knowledgeable instructor and knows ways to make stuff easy to understand. Show more Show less Instructors Kirill Eremenko Data Scientist 4.5 Instructor Rating 502,545 Reviews 1,843,224 Students 45 Courses My name is Kirill Eremenko and I am super-psyched that you are reading this! Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes. From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events. To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you! Show more Show less Ligency Team Helping Data Scientists Succeed 4.5 Instructor Rating 510,085 Reviews 1,809,544 Students 119 Courses Hi there, We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more! We are here to help you stay on the cutting edge of Data Science and Technology. See you in class, Sincerely, The Real People at Ligency Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6776ed3acaf653eb',m:'33edd50905eea3a8908ed7bac1fbf8062b3ab11c-1627735558-1800-ASWJFGF00dis7WmX0/l8bYnTXZqDkjM1tWcZ/9HC0HmRme9hGGecosWqQo+J7Ff/go+tVjC9tLMFTSWNM10cg96xqCZrGuzNAWLTSUyPVCyDp65FCrVejovHtznACIs7+nXFLRt2IN/eMw+5pFGfwV4=',s:[0x982d9765f6,0xc8fb42d932],}})();
  4. Learn how to create variables Learn about integer, float, logical, string and other types in Python Learn how to create a while() loop and a for() loop in Python Learn how to install packages in Python Understand the Law of Large Numbers Curated for the Udemy Business collection Course content 8 sections • 75 lectures • 11h 10m total length Expand all sections Welcome To The Course 6 lectures • 13min Installing Python (Windows & MAC) Preview 08:55 BONUS: Learning Paths 00:34 Get the materials 00:05 Some Additional Resources!! 00:13 FAQBot! 01:28 Your Shortcut To Becoming A Better Data Scientist! 02:05 Core Programming Principles 10 lectures • 1hr 14min Updates on Udemy Reviews 01:09 Types of variables 08:44 Using Variables 08:58 Boolean Variables and Operators 06:03 The "While" Loop 09:56 The "For" Loop 07:57 The "If" statement Preview 12:29 Code indentation in Python 02:40 Section recap 03:08 HOMEWORK: Law of Large Numbers 12:51 Core Programming Principles 5 questions Fundamentals Of Python 11 lectures • 1hr 18min What is a List? 03:15 Let's create some lists 08:42 Using the [] brackets 06:28 Slicing 09:27 Tuples in Python 06:17 Functions in Python 05:37 Packages in Python Preview 13:39 Numpy and Arrays in Python 07:08 Slicing Arrays 04:32 Section Recap 03:06 HOMEWORK: Financial Statement Analysis 10:11 Fundamentals of Python 5 questions Matrices 12 lectures • 1hr 59min Project Brief: Basketball Trends 08:16 Matrices Preview 03:31 Building Your First Matrix 16:50 Dictionaries in Python 14:20 Matrix Operations 08:34 Your first visualization 11:04 Expanded Visualization 09:37 Creating Your First Function 11:09 Advanced Function Design 11:15 Basketball Insights Preview 11:17 Section Recap 04:07 HOMEWORK: Basketball free throws 08:43 Matrices 5 questions Data Frames 12 lectures • 1hr 59min Importing data into Python Preview 08:25 Exploring your dataset 10:51 Renaming Columns of a Dataframe 02:56 Subsetting dataframes in Pandas 16:31 Basic operations with a Data Frame 09:49 Filtering a Data Frame 18:52 Using .at() and .iat() (advanced tutorial) 09:01 Introduction to Seaborn Preview 10:47 Visualizing With Seaborn: Part 1 10:05 Keyword Arguments in Python (advanced tutorial) 10:42 Section Recap 04:30 HOMEWORK: World Trends 06:57 Data Frames 5 questions Advanced Visualization 14 lectures • 2hr 36min What is a Category data type? 10:29 Working with JointPlots 07:38 Histograms 07:52 Stacked histograms in Python 18:29 Creating a KDE Plot 07:59 Working with Subplots() 14:05 Violinplots vs Boxplots Preview 08:55 Creating a Facet Grid 12:28 Coordinates and Diagonals 07:54 BONUS: Building Dashboards in Python 16:31 BONUS: Styling Tips Preview 15:46 BONUS: Finishing Touches 14:48 Section Recap 05:37 HOMEWORK: Movie Domestic % Gross 07:57 Advanced Visualization 5 questions Homework Solutions 9 lectures • 1hr 49min Homework Solution Section 2: Law Of Large Numbers 08:57 Homework Solution Section 3: Financial Statement Analysis (Part 1) 10:30 Homework Solution Section 3: Financial Statement Analysis (Part 2) 13:39 Homework Solution Section 4: Basketball Free Throws 17:23 Homework Solution Section 5: World Trends (Part 1) 15:45 Homework Solution Section 5: World Trends (Part 2) 14:35 Homework Solution Section 6: Movie Domestic % Gross (Part 1) 16:46 Homework Solution Section 6: Movie Domestic % Gross (Part 2) 08:19 THANK YOU bonus video 02:40 Bonus Lectures 1 lecture • 2min ***YOUR SPECIAL BONUS*** 02:02 Requirements No prior knowledge or experience needed. Only a passion to be successful! Description Learn Python Programming by doing! There are lots of Python courses and lectures out there. However, Python has a very steep learning curve and students often get overwhelmed. This course is different! This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward. After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples. This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises. In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course! I can't wait to see you in class, Sincerely, Kirill Eremenko Who this course is for: This course if for you if you want to learn how to program in Python This course is for you if you are tired of Python courses that are too complicated This course is for you if you want to learn Python by doing This course is for you if you like exciting challenges You WILL have homework in this course so you have to be prepared to work on it Show more Show less Featured review HIMANSHU SHEKHAR 4 courses 1 review Rating: 5.0 out of 5 a year ago The instructor have a really good way to explain everything and if you want to learn from scratch, you can go ahead with this course. Update after 50%: Kirrill is knowledgeable instructor and knows ways to make stuff easy to understand. Show more Show less Instructors Kirill Eremenko Data Scientist 4.5 Instructor Rating 502,545 Reviews 1,843,224 Students 45 Courses My name is Kirill Eremenko and I am super-psyched that you are reading this! Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes. From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events. To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you! Show more Show less Ligency Team Helping Data Scientists Succeed 4.5 Instructor Rating 510,085 Reviews 1,809,544 Students 119 Courses Hi there, We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more! We are here to help you stay on the cutting edge of Data Science and Technology. See you in class, Sincerely, The Real People at Ligency Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6776ed3acaf653eb',m:'33edd50905eea3a8908ed7bac1fbf8062b3ab11c-1627735558-1800-ASWJFGF00dis7WmX0/l8bYnTXZqDkjM1tWcZ/9HC0HmRme9hGGecosWqQo+J7Ff/go+tVjC9tLMFTSWNM10cg96xqCZrGuzNAWLTSUyPVCyDp65FCrVejovHtznACIs7+nXFLRt2IN/eMw+5pFGfwV4=',s:[0x982d9765f6,0xc8fb42d932],}})();
  5. Learn about integer, float, logical, string and other types in Python Learn how to create a while() loop and a for() loop in Python Learn how to install packages in Python Understand the Law of Large Numbers Curated for the Udemy Business collection Course content 8 sections • 75 lectures • 11h 10m total length Expand all sections Welcome To The Course 6 lectures • 13min Installing Python (Windows & MAC) Preview 08:55 BONUS: Learning Paths 00:34 Get the materials 00:05 Some Additional Resources!! 00:13 FAQBot! 01:28 Your Shortcut To Becoming A Better Data Scientist! 02:05 Core Programming Principles 10 lectures • 1hr 14min Updates on Udemy Reviews 01:09 Types of variables 08:44 Using Variables 08:58 Boolean Variables and Operators 06:03 The "While" Loop 09:56 The "For" Loop 07:57 The "If" statement Preview 12:29 Code indentation in Python 02:40 Section recap 03:08 HOMEWORK: Law of Large Numbers 12:51 Core Programming Principles 5 questions Fundamentals Of Python 11 lectures • 1hr 18min What is a List? 03:15 Let's create some lists 08:42 Using the [] brackets 06:28 Slicing 09:27 Tuples in Python 06:17 Functions in Python 05:37 Packages in Python Preview 13:39 Numpy and Arrays in Python 07:08 Slicing Arrays 04:32 Section Recap 03:06 HOMEWORK: Financial Statement Analysis 10:11 Fundamentals of Python 5 questions Matrices 12 lectures • 1hr 59min Project Brief: Basketball Trends 08:16 Matrices Preview 03:31 Building Your First Matrix 16:50 Dictionaries in Python 14:20 Matrix Operations 08:34 Your first visualization 11:04 Expanded Visualization 09:37 Creating Your First Function 11:09 Advanced Function Design 11:15 Basketball Insights Preview 11:17 Section Recap 04:07 HOMEWORK: Basketball free throws 08:43 Matrices 5 questions Data Frames 12 lectures • 1hr 59min Importing data into Python Preview 08:25 Exploring your dataset 10:51 Renaming Columns of a Dataframe 02:56 Subsetting dataframes in Pandas 16:31 Basic operations with a Data Frame 09:49 Filtering a Data Frame 18:52 Using .at() and .iat() (advanced tutorial) 09:01 Introduction to Seaborn Preview 10:47 Visualizing With Seaborn: Part 1 10:05 Keyword Arguments in Python (advanced tutorial) 10:42 Section Recap 04:30 HOMEWORK: World Trends 06:57 Data Frames 5 questions Advanced Visualization 14 lectures • 2hr 36min What is a Category data type? 10:29 Working with JointPlots 07:38 Histograms 07:52 Stacked histograms in Python 18:29 Creating a KDE Plot 07:59 Working with Subplots() 14:05 Violinplots vs Boxplots Preview 08:55 Creating a Facet Grid 12:28 Coordinates and Diagonals 07:54 BONUS: Building Dashboards in Python 16:31 BONUS: Styling Tips Preview 15:46 BONUS: Finishing Touches 14:48 Section Recap 05:37 HOMEWORK: Movie Domestic % Gross 07:57 Advanced Visualization 5 questions Homework Solutions 9 lectures • 1hr 49min Homework Solution Section 2: Law Of Large Numbers 08:57 Homework Solution Section 3: Financial Statement Analysis (Part 1) 10:30 Homework Solution Section 3: Financial Statement Analysis (Part 2) 13:39 Homework Solution Section 4: Basketball Free Throws 17:23 Homework Solution Section 5: World Trends (Part 1) 15:45 Homework Solution Section 5: World Trends (Part 2) 14:35 Homework Solution Section 6: Movie Domestic % Gross (Part 1) 16:46 Homework Solution Section 6: Movie Domestic % Gross (Part 2) 08:19 THANK YOU bonus video 02:40 Bonus Lectures 1 lecture • 2min ***YOUR SPECIAL BONUS*** 02:02 Requirements No prior knowledge or experience needed. Only a passion to be successful! Description Learn Python Programming by doing! There are lots of Python courses and lectures out there. However, Python has a very steep learning curve and students often get overwhelmed. This course is different! This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward. After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples. This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises. In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course! I can't wait to see you in class, Sincerely, Kirill Eremenko Who this course is for: This course if for you if you want to learn how to program in Python This course is for you if you are tired of Python courses that are too complicated This course is for you if you want to learn Python by doing This course is for you if you like exciting challenges You WILL have homework in this course so you have to be prepared to work on it Show more Show less Featured review HIMANSHU SHEKHAR 4 courses 1 review Rating: 5.0 out of 5 a year ago The instructor have a really good way to explain everything and if you want to learn from scratch, you can go ahead with this course. Update after 50%: Kirrill is knowledgeable instructor and knows ways to make stuff easy to understand. Show more Show less Instructors Kirill Eremenko Data Scientist 4.5 Instructor Rating 502,545 Reviews 1,843,224 Students 45 Courses My name is Kirill Eremenko and I am super-psyched that you are reading this! Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes. From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events. To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you! Show more Show less Ligency Team Helping Data Scientists Succeed 4.5 Instructor Rating 510,085 Reviews 1,809,544 Students 119 Courses Hi there, We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more! We are here to help you stay on the cutting edge of Data Science and Technology. See you in class, Sincerely, The Real People at Ligency Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6776ed3acaf653eb',m:'33edd50905eea3a8908ed7bac1fbf8062b3ab11c-1627735558-1800-ASWJFGF00dis7WmX0/l8bYnTXZqDkjM1tWcZ/9HC0HmRme9hGGecosWqQo+J7Ff/go+tVjC9tLMFTSWNM10cg96xqCZrGuzNAWLTSUyPVCyDp65FCrVejovHtznACIs7+nXFLRt2IN/eMw+5pFGfwV4=',s:[0x982d9765f6,0xc8fb42d932],}})();
  6. Learn how to create a while() loop and a for() loop in Python Learn how to install packages in Python Understand the Law of Large Numbers Curated for the Udemy Business collection Course content 8 sections • 75 lectures • 11h 10m total length Expand all sections Welcome To The Course 6 lectures • 13min Installing Python (Windows & MAC) Preview 08:55 BONUS: Learning Paths 00:34 Get the materials 00:05 Some Additional Resources!! 00:13 FAQBot! 01:28 Your Shortcut To Becoming A Better Data Scientist! 02:05 Core Programming Principles 10 lectures • 1hr 14min Updates on Udemy Reviews 01:09 Types of variables 08:44 Using Variables 08:58 Boolean Variables and Operators 06:03 The "While" Loop 09:56 The "For" Loop 07:57 The "If" statement Preview 12:29 Code indentation in Python 02:40 Section recap 03:08 HOMEWORK: Law of Large Numbers 12:51 Core Programming Principles 5 questions Fundamentals Of Python 11 lectures • 1hr 18min What is a List? 03:15 Let's create some lists 08:42 Using the [] brackets 06:28 Slicing 09:27 Tuples in Python 06:17 Functions in Python 05:37 Packages in Python Preview 13:39 Numpy and Arrays in Python 07:08 Slicing Arrays 04:32 Section Recap 03:06 HOMEWORK: Financial Statement Analysis 10:11 Fundamentals of Python 5 questions Matrices 12 lectures • 1hr 59min Project Brief: Basketball Trends 08:16 Matrices Preview 03:31 Building Your First Matrix 16:50 Dictionaries in Python 14:20 Matrix Operations 08:34 Your first visualization 11:04 Expanded Visualization 09:37 Creating Your First Function 11:09 Advanced Function Design 11:15 Basketball Insights Preview 11:17 Section Recap 04:07 HOMEWORK: Basketball free throws 08:43 Matrices 5 questions Data Frames 12 lectures • 1hr 59min Importing data into Python Preview 08:25 Exploring your dataset 10:51 Renaming Columns of a Dataframe 02:56 Subsetting dataframes in Pandas 16:31 Basic operations with a Data Frame 09:49 Filtering a Data Frame 18:52 Using .at() and .iat() (advanced tutorial) 09:01 Introduction to Seaborn Preview 10:47 Visualizing With Seaborn: Part 1 10:05 Keyword Arguments in Python (advanced tutorial) 10:42 Section Recap 04:30 HOMEWORK: World Trends 06:57 Data Frames 5 questions Advanced Visualization 14 lectures • 2hr 36min What is a Category data type? 10:29 Working with JointPlots 07:38 Histograms 07:52 Stacked histograms in Python 18:29 Creating a KDE Plot 07:59 Working with Subplots() 14:05 Violinplots vs Boxplots Preview 08:55 Creating a Facet Grid 12:28 Coordinates and Diagonals 07:54 BONUS: Building Dashboards in Python 16:31 BONUS: Styling Tips Preview 15:46 BONUS: Finishing Touches 14:48 Section Recap 05:37 HOMEWORK: Movie Domestic % Gross 07:57 Advanced Visualization 5 questions Homework Solutions 9 lectures • 1hr 49min Homework Solution Section 2: Law Of Large Numbers 08:57 Homework Solution Section 3: Financial Statement Analysis (Part 1) 10:30 Homework Solution Section 3: Financial Statement Analysis (Part 2) 13:39 Homework Solution Section 4: Basketball Free Throws 17:23 Homework Solution Section 5: World Trends (Part 1) 15:45 Homework Solution Section 5: World Trends (Part 2) 14:35 Homework Solution Section 6: Movie Domestic % Gross (Part 1) 16:46 Homework Solution Section 6: Movie Domestic % Gross (Part 2) 08:19 THANK YOU bonus video 02:40 Bonus Lectures 1 lecture • 2min ***YOUR SPECIAL BONUS*** 02:02 Requirements No prior knowledge or experience needed. Only a passion to be successful! Description Learn Python Programming by doing! There are lots of Python courses and lectures out there. However, Python has a very steep learning curve and students often get overwhelmed. This course is different! This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward. After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples. This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises. In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course! I can't wait to see you in class, Sincerely, Kirill Eremenko Who this course is for: This course if for you if you want to learn how to program in Python This course is for you if you are tired of Python courses that are too complicated This course is for you if you want to learn Python by doing This course is for you if you like exciting challenges You WILL have homework in this course so you have to be prepared to work on it Show more Show less Featured review HIMANSHU SHEKHAR 4 courses 1 review Rating: 5.0 out of 5 a year ago The instructor have a really good way to explain everything and if you want to learn from scratch, you can go ahead with this course. Update after 50%: Kirrill is knowledgeable instructor and knows ways to make stuff easy to understand. Show more Show less Instructors Kirill Eremenko Data Scientist 4.5 Instructor Rating 502,545 Reviews 1,843,224 Students 45 Courses My name is Kirill Eremenko and I am super-psyched that you are reading this! Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes. From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events. To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you! Show more Show less Ligency Team Helping Data Scientists Succeed 4.5 Instructor Rating 510,085 Reviews 1,809,544 Students 119 Courses Hi there, We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more! We are here to help you stay on the cutting edge of Data Science and Technology. See you in class, Sincerely, The Real People at Ligency Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6776ed3acaf653eb',m:'33edd50905eea3a8908ed7bac1fbf8062b3ab11c-1627735558-1800-ASWJFGF00dis7WmX0/l8bYnTXZqDkjM1tWcZ/9HC0HmRme9hGGecosWqQo+J7Ff/go+tVjC9tLMFTSWNM10cg96xqCZrGuzNAWLTSUyPVCyDp65FCrVejovHtznACIs7+nXFLRt2IN/eMw+5pFGfwV4=',s:[0x982d9765f6,0xc8fb42d932],}})();
  7. Learn how to install packages in Python Understand the Law of Large Numbers Curated for the Udemy Business collection Course content 8 sections • 75 lectures • 11h 10m total length Expand all sections Welcome To The Course 6 lectures • 13min Installing Python (Windows & MAC) Preview 08:55 BONUS: Learning Paths 00:34 Get the materials 00:05 Some Additional Resources!! 00:13 FAQBot! 01:28 Your Shortcut To Becoming A Better Data Scientist! 02:05 Core Programming Principles 10 lectures • 1hr 14min Updates on Udemy Reviews 01:09 Types of variables 08:44 Using Variables 08:58 Boolean Variables and Operators 06:03 The "While" Loop 09:56 The "For" Loop 07:57 The "If" statement Preview 12:29 Code indentation in Python 02:40 Section recap 03:08 HOMEWORK: Law of Large Numbers 12:51 Core Programming Principles 5 questions Fundamentals Of Python 11 lectures • 1hr 18min What is a List? 03:15 Let's create some lists 08:42 Using the [] brackets 06:28 Slicing 09:27 Tuples in Python 06:17 Functions in Python 05:37 Packages in Python Preview 13:39 Numpy and Arrays in Python 07:08 Slicing Arrays 04:32 Section Recap 03:06 HOMEWORK: Financial Statement Analysis 10:11 Fundamentals of Python 5 questions Matrices 12 lectures • 1hr 59min Project Brief: Basketball Trends 08:16 Matrices Preview 03:31 Building Your First Matrix 16:50 Dictionaries in Python 14:20 Matrix Operations 08:34 Your first visualization 11:04 Expanded Visualization 09:37 Creating Your First Function 11:09 Advanced Function Design 11:15 Basketball Insights Preview 11:17 Section Recap 04:07 HOMEWORK: Basketball free throws 08:43 Matrices 5 questions Data Frames 12 lectures • 1hr 59min Importing data into Python Preview 08:25 Exploring your dataset 10:51 Renaming Columns of a Dataframe 02:56 Subsetting dataframes in Pandas 16:31 Basic operations with a Data Frame 09:49 Filtering a Data Frame 18:52 Using .at() and .iat() (advanced tutorial) 09:01 Introduction to Seaborn Preview 10:47 Visualizing With Seaborn: Part 1 10:05 Keyword Arguments in Python (advanced tutorial) 10:42 Section Recap 04:30 HOMEWORK: World Trends 06:57 Data Frames 5 questions Advanced Visualization 14 lectures • 2hr 36min What is a Category data type? 10:29 Working with JointPlots 07:38 Histograms 07:52 Stacked histograms in Python 18:29 Creating a KDE Plot 07:59 Working with Subplots() 14:05 Violinplots vs Boxplots Preview 08:55 Creating a Facet Grid 12:28 Coordinates and Diagonals 07:54 BONUS: Building Dashboards in Python 16:31 BONUS: Styling Tips Preview 15:46 BONUS: Finishing Touches 14:48 Section Recap 05:37 HOMEWORK: Movie Domestic % Gross 07:57 Advanced Visualization 5 questions Homework Solutions 9 lectures • 1hr 49min Homework Solution Section 2: Law Of Large Numbers 08:57 Homework Solution Section 3: Financial Statement Analysis (Part 1) 10:30 Homework Solution Section 3: Financial Statement Analysis (Part 2) 13:39 Homework Solution Section 4: Basketball Free Throws 17:23 Homework Solution Section 5: World Trends (Part 1) 15:45 Homework Solution Section 5: World Trends (Part 2) 14:35 Homework Solution Section 6: Movie Domestic % Gross (Part 1) 16:46 Homework Solution Section 6: Movie Domestic % Gross (Part 2) 08:19 THANK YOU bonus video 02:40 Bonus Lectures 1 lecture • 2min ***YOUR SPECIAL BONUS*** 02:02 Requirements No prior knowledge or experience needed. Only a passion to be successful! Description Learn Python Programming by doing! There are lots of Python courses and lectures out there. However, Python has a very steep learning curve and students often get overwhelmed. This course is different! This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward. After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples. This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises. In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course! I can't wait to see you in class, Sincerely, Kirill Eremenko Who this course is for: This course if for you if you want to learn how to program in Python This course is for you if you are tired of Python courses that are too complicated This course is for you if you want to learn Python by doing This course is for you if you like exciting challenges You WILL have homework in this course so you have to be prepared to work on it Show more Show less Featured review HIMANSHU SHEKHAR 4 courses 1 review Rating: 5.0 out of 5 a year ago The instructor have a really good way to explain everything and if you want to learn from scratch, you can go ahead with this course. Update after 50%: Kirrill is knowledgeable instructor and knows ways to make stuff easy to understand. Show more Show less Instructors Kirill Eremenko Data Scientist 4.5 Instructor Rating 502,545 Reviews 1,843,224 Students 45 Courses My name is Kirill Eremenko and I am super-psyched that you are reading this! Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes. From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events. To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you! Show more Show less Ligency Team Helping Data Scientists Succeed 4.5 Instructor Rating 510,085 Reviews 1,809,544 Students 119 Courses Hi there, We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more! We are here to help you stay on the cutting edge of Data Science and Technology. See you in class, Sincerely, The Real People at Ligency Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6776ed3acaf653eb',m:'33edd50905eea3a8908ed7bac1fbf8062b3ab11c-1627735558-1800-ASWJFGF00dis7WmX0/l8bYnTXZqDkjM1tWcZ/9HC0HmRme9hGGecosWqQo+J7Ff/go+tVjC9tLMFTSWNM10cg96xqCZrGuzNAWLTSUyPVCyDp65FCrVejovHtznACIs7+nXFLRt2IN/eMw+5pFGfwV4=',s:[0x982d9765f6,0xc8fb42d932],}})();
  8. Understand the Law of Large Numbers Curated for the Udemy Business collection Course content 8 sections • 75 lectures • 11h 10m total length Expand all sections Welcome To The Course 6 lectures • 13min Installing Python (Windows & MAC) Preview 08:55 BONUS: Learning Paths 00:34 Get the materials 00:05 Some Additional Resources!! 00:13 FAQBot! 01:28 Your Shortcut To Becoming A Better Data Scientist! 02:05 Core Programming Principles 10 lectures • 1hr 14min Updates on Udemy Reviews 01:09 Types of variables 08:44 Using Variables 08:58 Boolean Variables and Operators 06:03 The "While" Loop 09:56 The "For" Loop 07:57 The "If" statement Preview 12:29 Code indentation in Python 02:40 Section recap 03:08 HOMEWORK: Law of Large Numbers 12:51 Core Programming Principles 5 questions Fundamentals Of Python 11 lectures • 1hr 18min What is a List? 03:15 Let's create some lists 08:42 Using the [] brackets 06:28 Slicing 09:27 Tuples in Python 06:17 Functions in Python 05:37 Packages in Python Preview 13:39 Numpy and Arrays in Python 07:08 Slicing Arrays 04:32 Section Recap 03:06 HOMEWORK: Financial Statement Analysis 10:11 Fundamentals of Python 5 questions Matrices 12 lectures • 1hr 59min Project Brief: Basketball Trends 08:16 Matrices Preview 03:31 Building Your First Matrix 16:50 Dictionaries in Python 14:20 Matrix Operations 08:34 Your first visualization 11:04 Expanded Visualization 09:37 Creating Your First Function 11:09 Advanced Function Design 11:15 Basketball Insights Preview 11:17 Section Recap 04:07 HOMEWORK: Basketball free throws 08:43 Matrices 5 questions Data Frames 12 lectures • 1hr 59min Importing data into Python Preview 08:25 Exploring your dataset 10:51 Renaming Columns of a Dataframe 02:56 Subsetting dataframes in Pandas 16:31 Basic operations with a Data Frame 09:49 Filtering a Data Frame 18:52 Using .at() and .iat() (advanced tutorial) 09:01 Introduction to Seaborn Preview 10:47 Visualizing With Seaborn: Part 1 10:05 Keyword Arguments in Python (advanced tutorial) 10:42 Section Recap 04:30 HOMEWORK: World Trends 06:57 Data Frames 5 questions Advanced Visualization 14 lectures • 2hr 36min What is a Category data type? 10:29 Working with JointPlots 07:38 Histograms 07:52 Stacked histograms in Python 18:29 Creating a KDE Plot 07:59 Working with Subplots() 14:05 Violinplots vs Boxplots Preview 08:55 Creating a Facet Grid 12:28 Coordinates and Diagonals 07:54 BONUS: Building Dashboards in Python 16:31 BONUS: Styling Tips Preview 15:46 BONUS: Finishing Touches 14:48 Section Recap 05:37 HOMEWORK: Movie Domestic % Gross 07:57 Advanced Visualization 5 questions Homework Solutions 9 lectures • 1hr 49min Homework Solution Section 2: Law Of Large Numbers 08:57 Homework Solution Section 3: Financial Statement Analysis (Part 1) 10:30 Homework Solution Section 3: Financial Statement Analysis (Part 2) 13:39 Homework Solution Section 4: Basketball Free Throws 17:23 Homework Solution Section 5: World Trends (Part 1) 15:45 Homework Solution Section 5: World Trends (Part 2) 14:35 Homework Solution Section 6: Movie Domestic % Gross (Part 1) 16:46 Homework Solution Section 6: Movie Domestic % Gross (Part 2) 08:19 THANK YOU bonus video 02:40 Bonus Lectures 1 lecture • 2min ***YOUR SPECIAL BONUS*** 02:02 Requirements No prior knowledge or experience needed. Only a passion to be successful! Description Learn Python Programming by doing! There are lots of Python courses and lectures out there. However, Python has a very steep learning curve and students often get overwhelmed. This course is different! This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward. After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples. This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises. In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course! I can't wait to see you in class, Sincerely, Kirill Eremenko Who this course is for: This course if for you if you want to learn how to program in Python This course is for you if you are tired of Python courses that are too complicated This course is for you if you want to learn Python by doing This course is for you if you like exciting challenges You WILL have homework in this course so you have to be prepared to work on it Show more Show less Featured review HIMANSHU SHEKHAR 4 courses 1 review Rating: 5.0 out of 5 a year ago The instructor have a really good way to explain everything and if you want to learn from scratch, you can go ahead with this course. Update after 50%: Kirrill is knowledgeable instructor and knows ways to make stuff easy to understand. Show more Show less Instructors Kirill Eremenko Data Scientist 4.5 Instructor Rating 502,545 Reviews 1,843,224 Students 45 Courses My name is Kirill Eremenko and I am super-psyched that you are reading this! Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes. From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events. To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you! Show more Show less Ligency Team Helping Data Scientists Succeed 4.5 Instructor Rating 510,085 Reviews 1,809,544 Students 119 Courses Hi there, We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more! We are here to help you stay on the cutting edge of Data Science and Technology. See you in class, Sincerely, The Real People at Ligency Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'6776ed3acaf653eb',m:'33edd50905eea3a8908ed7bac1fbf8062b3ab11c-1627735558-1800-ASWJFGF00dis7WmX0/l8bYnTXZqDkjM1tWcZ/9HC0HmRme9hGGecosWqQo+J7Ff/go+tVjC9tLMFTSWNM10cg96xqCZrGuzNAWLTSUyPVCyDp65FCrVejovHtznACIs7+nXFLRt2IN/eMw+5pFGfwV4=',s:[0x982d9765f6,0xc8fb42d932],}})();