Detailed Course Syllabus
Module 1: Data Analytics & Mathematical Foundations
Phase 1- ✓Python for Data Science - Advanced data structures, list comprehensions, and lambdas
- ✓Scientific Libraries - Numerical computation with NumPy & data manipulation with Pandas
- ✓Exploratory Data Analysis (EDA) - Statistical visualizations using Matplotlib & Seaborn
- ✓Mathematics & Statistics - Probability distributions, linear algebra, hypothesis testing, and regression analysis
Module 2: Core Machine Learning
Phase 2- ✓Supervised Learning - Linear/Logistic Regression, Decision Trees, Random Forests, and SVMs
- ✓Unsupervised Learning - K-Means Clustering, Hierarchical Clustering, and Principal Component Analysis (PCA)
- ✓Model Evaluation & Tuning - Hyperparameter tuning (GridSearchCV), Cross-Validation, and Confusion Matrix metrics
- ✓Feature Engineering - Encoding, scaling, handling missing values, and dimensional reduction
Module 3: Neural Networks & Deep Learning
Phase 3- ✓Deep Learning Basics - Artificial Neural Networks (ANN), activation functions, and backpropagation
- ✓Computer Vision - Convolutional Neural Networks (CNN) for image recognition and processing
- ✓Natural Language Processing (NLP) - Text preprocessing, Tokenization, TF-IDF, and Recurrent Neural Networks (RNN)
- ✓Frameworks - Creating and training models using TensorFlow/Keras and PyTorch
Module 4: Generative AI & BI Visualization
Phase 4- ✓Generative AI & LLMs - Integration of OpenAI API, prompt engineering, and LangChain embeddings
- ✓Business Intelligence - Creating interactive, publication-quality dashboards in Tableau and PowerBI
- ✓Model Deployment - Building and deploying an ML app using Streamlit on Heroku/AWS Cloud
- ✓Capstone Project - Building an end-to-end predictive analysis or GenAI model on real-world Kaggle datasets
Download Official Syllabus
Get a comprehensive offline PDF of this syllabus containing all lesson outcomes, lab assignments, and prerequisites.
Download CurriculumCourse Key Highlights
- Python Libraries (NumPy, Pandas, Matplotlib)
- Supervised & Unsupervised Machine Learning
- Natural Language Processing (NLP) & GenAI
- Interactive Dashboards (Tableau, PowerBI)
- 100% Practical Hands-on Sandbox Labs
- Mock Technical Interviews & Resume Auditing
Request Callback / Enquiry
Fill out your details below and an admissions counselor will reach out to you within 24 hours.