Python with Data Science (AI & ML) – 40 Sessions Plan

Plotting for exploratory data analysis (EDA)

Linear Algebra

Probability and Statistics

Dimensionality reduction and Visualization:

PCA(principal component analysis)

(t·SNE}T-distributed Stochastic Neighborhood Embedding

Statistical Testing

Sample Interview Questions

Introduction to Machine Learning

Performance measurement of models

Classification And Regression Models: K Nearest Neighbors

Naive Baye’s

Linear Regression

Logistic Regression

Classification algorithms in various situations

Real world problem: Predict rating on given product reviews on Amazon

Sample Interview Questions

Support vectorMachines (SVM)

Decision Trees

Ensemble Models

Deployment of ML Models

Sample Interview Questions

Case Study 1: Quora question PairSimilarity Problem

Case Study 2: Personalized Cancer Diagnosis

Case Study 3: Facebook FriendRecommendation using Graph Mining

Case study 4: Taxi demand prediction in NewYork City

Case study 5: Stack overflow tag predictor

Unsupervised learning/Clustering

Hierarchical clusteringTechnique

DBSCAN (Density basedclustering) Technique

Recommender Systems and Matrix Factorization

Interview Questions on Recommender Systems and Matrix Factorization.

Case Study 6: Amazon fashion discovery engine (Content basedrecommendation)

Case Study 7: Netflix Movie Recommendation System(Collaborative based recommendation)

Case Study 8: Music Recommendation system

Sample Interview Questions

Deep Learning: NeuralNetworks

Deep Learning: Deep Multilayer perceptron's

Deep Learning: Tensor Flow and Keras.

Deep Learning: Convolutional Neural Nets.

Deep Learning: Long Short-term memory (LSTMs)

Deep Learning: Generative Adversarial Networks(GANS) Encoder-Decoder Models

Deep Learning: Image Segmentation

Deep learning: Object Detection

OpenCV using Python

Interview Questions on Deep Learning

Case Study 10: Human Activity Recognition

Case Study 11: Self Driving Car

Case Study 12: Music Generation using Deep learning

Case Study 13: Building a Smart Gym Assistant from scratch

Attention Models in Deep learning Deep Learning: Transformers and BERT

Deep Learning: GPT•l, 2 and GPT·3 Models

Sample Interview Questions