Week 1
Introduction to Python Programming Language

• Lists
• Sets
• Tuples
• Dictionaries

Week 2
Introduction to Python for Data Science

• Numpy
• Pandas
• Advanced Pandas Tricks
• Exploratory Data Analysis
• Data Cleaning
• Data Preparation

Week 3
Introduction to Data Analysis

• Groupby
• Aggregate Functions
• Lambas
• Functions
• Classes
• Definitions
• Filter
• Matrices
• Queries
• Data Frame Operations

Week 4
Introduction to Data Visualization

• Introduction to Pandas for Plotting
• Types of Charts
• Univariate Analysis
• Bivariate Analysis
• Multivariate Analysis
• Matplotlib
• Seaborn
• Plotly
• Animated Data Visualizations
• Geo Spatial Data Visualizations
• Creating Dashboards in Python

Week 5
Introduction to Data Preprocessing

• Feature Engineering
• Feature Extraction
• Feature Selection Strategies
• Types of Feature Selection
• Correlation
• Heatmaps
• Data Preparation
• Data Manipulation

Week 6
Introduction to Machine Learning

• Introduction to Types of Machine Learning
• Supervised Learning Techniques
• Regression Analysis
• Linear Regression
• Lasso Regression
• Ridge Regression
• Elastic Net Regression
• Metrics for Regression

Week 7
Introduction to Classification Algorithms

• Logistic Regression
• Decision Trees
• Random Forests
• K Nearest Neighbors
• Support Vector Machines
• Naive Bayes Theorem
• Ada Boost
• Metrics for Classification

Week 8
Introduction to Unsupervised Learning

• Types of Clustering Techniques
• K-Means Clustering
• Hierarchial Clustering
• Dimensionality Reduction Techniques
• PCA
• LDA
• Difference between LDA and PCA

Week 9
Introduction to Advanced Machine Learning Tricks

• Cross Validation Techniques
• Grid Search
• Hyper Parameter Tuning
• Ensembling Techniques
• Model Validation Techniques
• Model Explanation