English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 73 lectures (11h 7m) | 6.48 GB
Programming In Python For Data Analytics And Data Science. Learn Statistical Analysis, Data Mining And Visualization
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,
What you will learn:
- Learn the core principles of programming
- Learn how to create variables
- How to visualize data in Seaborn
- How to create histograms, KDE plots, violin plots and style your charts to perfection
- Learn about integer, float, logical, string and other types in Python
- Learn how to create a while() loop and a for() loop in Python
- And much more….
Table of Contents
Welcome To The Course
1 Welcome Challenge
2 Installing Python Windows MAC
3 Get the Datasets here
4 Extra Resources
Core Programming Principles
5 Types of variables
6 Using Variables
7 Boolean Variables and Operators
8 The While Loop
9 The For Loop
10 The If statement
11 Code indentation in Python
12 Section recap
13 HOMEWORK Law of Large Numbers
Fundamentals Of Python
14 What is a List
15 Lets create some lists
16 Using the brackets
17 Slicing
18 Tuples in Python
19 Functions in Python
20 Packages in Python
21 Numpy and Arrays in Python
22 Slicing Arrays
23 Section Recap
24 HOMEWORK Financial Statement Analysis
Matrices
25 Project Brief Basketball Trends
26 Matrices
27 Building Your First Matrix
28 Matrix Operations
29 Your first visualization
30 Dictionaries in Python
31 Expanded Visualization
32 Creating Your First Function
33 Advanced Function Design
34 Basketball Insights
35 Section Recap
36 HOMEWORK Basketball free throws
Data Frames
37 Importing data into Python
38 Exploring your dataset
39 Renaming Columns of a Dataframe
40 Subsetting dataframes in Pandas
41 Basic operations with a Data Frame
42 Filtering a Data Frame
43 Using at and iat advanced tutorial
44 Introduction to Seaborn
45 Visualizing With Seaborn Part 1
46 Keyword Arguments in Python advanced tutorial
47 Section Recap
48 HOMEWORK World Trends
Advanced Visualization
49 What is a Category data type
50 Working with JointPlots
51 Histograms
52 Stacked histograms in Python
53 Creating a KDE Plot
54 Working with Subplots
55 Violinplots vs Boxplots
56 Creating a Facet Grid
57 Coordinates and Diagonals
58 EXTRA Building Dashboards in Python
59 EXTRA Styling Tips
60 EXTRA Finishing Touches
61 Section Recap
62 HOMEWORK Movie Domestic Gross
Homework Solutions
63 Homework Solution Section 2 Law Of Large Numbers
64 Homework Solution Section 3 Financial Statement Analysis Part 1
65 Homework Solution Section 3 Financial Statement Analysis Part 2
66 Homework Solution Section 4 Basketball Free Throws
67 Homework Solution Section 5 World Trends Part 1
68 Homework Solution Section 5 World Trends Part 2
69 Homework Solution Section 6 Movie Domestic Gross Part 1
70 Homework Solution Section 6 Movie Domestic Gross Part 2
71 THANK YOU Video
Congratulations Dont forget your Prize
72 Huge Congrats for completing the challenge
73 Bonus How To UNLOCK Top Salaries Live Training
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