SGLearn@Python A-Z™: Python For Data Science
4.6 (2 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
6 students enrolled

SGLearn@Python A-Z™: Python For Data Science

Programming In Python For Data Analytics And Data Science. Learn Statistical Analysis, Data Mining And Visualization
4.6 (2 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
6 students enrolled
Last updated 7/2017
English
Price: $199.99
30-Day Money-Back Guarantee
This course includes
  • 11 hours on-demand video
  • 1 article
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • 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
Course content
Expand all 68 lectures 11:02:36
+ Core Programming Principles
9 lectures 01:12:46
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
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 01:18:22
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
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 01:58:43
Project Brief: Basketball Trends
08:16
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
Section Recap
04:07
HOMEWORK: Basketball free throws
08:43
Matrices
5 questions
+ Data Frames
12 lectures 01:59:26
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
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 02:36:28
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
Creating a Facet Grid
12:28
Coordinates and Diagonals
07:54
BONUS: Building Dashboards in Python
16:31
BONUS: Finishing Touches
14:48
Section Recap
05:37
HOMEWORK: Movie Domestic % Gross
07:57
Advanced Visualization
5 questions
+ Homework Solutions
8 lectures 01:45:54
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
+ Bonus Lectures
1 lecture 02:01
***YOUR SPECIAL BONUS***
02:01
Requirements
  • No prior knowledge or experience needed. Only a passion to be successful!
Description

Welcome to the SGLearn Series targeted at Singapore-based learners picking up new skillsets and competencies. This course is an adaptation of the same course by Kirill Eremenko and is specially produced in collaboration with Kirill for Singaporean learners.

---------------

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