Introduction to AI
Machine Learning basics
Workflow of a Machine Learning projects
Introduction to Deep Learning and difference
between ML and DL
Inducing AI using ML and DL
How to choose an AI project?

Why python ?
Python IDE
Hello World Program
Variables & Names
String Basics
List
Tuple
Dictionaries
Conditional Statements
For and While Loop
Functions
Numbers and Math Functions
Common Errors in Python

Python - Advanced
Functions as Arguments
List Comprehension
File Handling
Debugging in Python
Class and Objects
Lambda, Filters and Map
Python PIP
Iterators
Pickling
Python JSON
Python API and web scraping

Introduction to Pandas
Series Data Structure - Querying and Indexing
DataFrame Data Structure - Querying, Indexing,
and loading
Merging data frames
Group by operation
Pivot table
Date/Time functionality
Example: Manipulating DataFrame

Data Modeling
Normalization, and Star Schema
ACID transactions
Select, insert, update & delete (DML and DQL)
Join operations
Window functions (rank, dense rank, row number
etc)
Data Types, Variables and Constants
Conditional Structures (IF, CASE, GOTO and NULL)
Integrating python with SQL

Structured vs Unstructured Data
Common Data issues and how to clean them
Textual data cleaning
Meaningful data transformation (Scaling and
Normalisation)
Handling missing data
Outlier detection and correction
Example: EDA on Movies DataSet

Read Complex JSON files
Styling Tabulation
Distribution of Data - Histogram
Box Plot
Pie Chart
Donut Chart
Stacked Bar Plot
Relative Stacked Bar Plot
Stacked Area Plot
Scatter Plots
Bar Plot
Continuous vs Continuous Plot
Line Plot
Line Plot Covid Data

What is ML and how is it related to AI?
Predictive Modeling
Correlation
Basics of regression
Ordinary least squares
Simple linear regression
Model building
Model assessment and improvement
Diagnostics
Multiple linear regression (model building and
assessment)
Random forest & decision tree

Classification
Logistic regression
K nearest neighbours
Clustering
K means
Dimensionality reduction methods
Principal component analysis and its variants
Linear Discriminant Analysis
Support vector machine

A single neuron details
The XOR problem and introduction to multi layer
perceptron
Understanding the output & Activation Functions
Derivatives of Activation Functions
Gradient Descent for Neural Networks
Backpropagation Algorithm
Understanding Computational graph
Backpropagation using computational graph
Random initialization

Deep L-layer Neural Network
Forward Propagation in a Deep Network
Building Blocks of Deep Neural Networks
Forward and Backward Propagation
Parameters vs Hyperparameters
Parameters learning and hyperparameters tuning

Understanding the learning aspect of neural
networks
PyTorch basics
Tensor and Datasets in PyTorch
Linear Regression in PyTorch
Multiple Input Output Linear Regression
Softmax Regression
Shallow Neural Networks
Splitting the data (train/test/dev)
Understanding Bias and Variance
Understanding overfitting
Using regularization
Regularization techniques (like dropout)

Implementing Deep Networks
Convolutional Neural Network (Convolution,
Activation Functions and Max Polling, Multiple
Input and Output Channels, GPU in PyTorch)
Normalizing Inputs
Vanishing / Exploding Gradients
Weight Initialization for Deep Networks
Numerical Approximation of Gradients
Gradient Checking
Gradient Checking Implementation

What is a CV? (understanding with examples)
Edge detection with examples
Padding
Strided Convolutions
Convolutions Over Volume
One Layer of a Convolutional Network
Simple Convolutional Network Example
Pooling Layers
CNN Example

Deep learning architectures for sequence
processing
Recurrent neural networks
Managing context in RNNs and its drawbacks
Introduction to LSTMs and GRUs

Self Attention Networks: Transformers
Introduction to Encoder-Decoder models
Encoder-Decoder with RNNs
Attention and Beam search
Encoder and Decoder with Transformers
Transfer Learning through Fine-Tuning