WSQ - Big Data Analytics and AI / Machine Learning with Python Coding / Programming (Beginner to Intermediate) Course Plan:

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• Learning Unit 1 - Write basic program with Python language (2hr)

• Numbers Data Type and Variables

• Strings and Printing

• Boolean Data Type

• Comparison and Logic Operators

 

• Learning Unit 2 - Write with different Python Data Structures (2hr)

• Lists

• Tuples

• Sets

• Dictionaries

 

• Learning Unit 3 - Write more complicated programs (2hr)

• Conditions and Branching

• Loops

• Functions

• Object-Oriented Programming

 

• Learning Unit 4 – Identify and employ appropriate statistical algorithms and data models (3hr)

• Describing variability

• Probability distributions

• Regression

 

• Learning Unit 5 - Apply Numpy library for Data Manipulation (2hr)

• Arrays

• Indexing and Selection

• Operations

 

• Learning Unit 6 - Apply Pandas library for Data Processing (2hr)

• Series and DataFrames

• Missing Data and GroupBy

• Algorithms using Concatenating, Merging, Joining

• Operations and Computational Methods

• Data Input and Output

 

• Learning Unit 7 - Apply Matplotlib library for Graphs and Data Visualization (3hr)

• Matplotlib Graphs

• Seaborn heatmap and pair plots

 

• Learning Unit 8 – Apply Scikit-Learn library for machine learning (3hr)

• Difference between AI, Machine Learning and Deep Machine Learning

• Training and Test Models with Scikit-Learn

 

• Learning Unit 9 – Combine different tools to solve real life problems (3hr)

• Identifying the problem

• Finding relevant data sources and deciding models to use

• Forming conclusions

• Pivoting due to unintended outcome

 

• Assessment (2hr)

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