- Intro to Python
- Data Structures in Python (List, Tuple, Set, Dictionary)
- Control Statements (Decision and Loops)
- Functions and Modules
- Object Oriented Programming
- Exception Handling
- File Handling
- Web API
- Databases
- List Comprehension, Lambda, Filter, Map, Reduce
- Problem Solving for Interviews
- Data Analytics Framework
- Numpy
- Pandas for Beginners
- Advance Pandas Operations
- Case Study - Pandas Manipulation
- Missing Value Treatment
- Visuallization Basics - Matplotlib and Seaborn
- Case Study - Covid_19_TimeSeries
- Plotly and Express
- Outliers - Coming Soon
- Normal Distribution
- Central Limit Theorem
- Hypothesis Testing
- Chi Square Testing
- Performing Statistical Test
- Data Preparation and Modelling with SKLearn
- Working with Text Data
- Working with Image Data
- Supervised ML Algorithms
- K - Nearest Neighbours
- Linear Regression
- Logistic Regression
- Gradient Descent
- Decision Trees
- Support Vector Machines
- Models with Feature Engineering
- Hyperparameter Tuning
- Ensembles - Unsupervised ML Algorithms
- Clustering
- Principal Component Analysis
- Model Serialization and Deserialization
- Application Integration
- MLFlow - Experiment Tracking and Model Management
- Prefect - Orchestrate ML Pipeline
- Car Price Prediction (Regression)
- Airline Sentiment Analysis (NLP - Classification)
- Adult Income Prediction (Classification)
- Web App Development + Serialization and Deserialization
- AWS Deployment
- Streamlit Heroku Deployment
- Customer Segmentation
- Web Scrapping
- Introduction to Deep Learning
- Training a Deep Neural Network + TensorFlow.Keras
- Convolutional Neural Network + TensorFlow.Keras
- Auto Encoders for Image Compression
- Recurrent Neural Network (Coming Soon)