Course Catalog & Syllabi
Every course is structured with Beginner, Intermediate, and Advanced sections, topic-level attendance, hands-on mini-tasks, and milestone projects.
Python — Basic to Advance
Master Python from ground zero to real-world applications. Covers variables, data structures, object-oriented programming, data analysis with NumPy/Pandas, REST APIs, and a live Streamlit AI analytics capstone.
Excel for Career Readiness
Master Microsoft Excel from essential formulas and conditional formatting to modern XLOOKUP, pivot tables, data cleaning, and dynamic executive dashboards.
Power BI — Data Visualization & Dashboards
Transform raw data into compelling interactive business intelligence reports. Learn Power Query ETL, Star Schema data modeling, DAX measures, time intelligence, and cloud publishing.
SQL — Database Fundamentals
Master relational databases, complex multi-table joins, subqueries, CTEs, analytical window functions, transactions, and normalized schema design using PostgreSQL and MySQL.
MongoDB — NoSQL Databases
Learn document databases from the ground up. Covers MongoDB Atlas, CRUD operations, Aggregation Pipelines ($match, $group, $lookup), schema design patterns, and indexing for high performance.
C Language — Systems Foundations
Master low-level programming, computer memory architecture, pointers, dynamic memory allocation (malloc/free), structs, and file I/O.
C++ — Object-Oriented & STL Mastery
Master Modern C++, Object-Oriented paradigms (Inheritance, Polymorphism, Abstraction), Standard Template Library (Vectors, Maps, Sets, Algorithms), and generic Templates.
Java — Core to Object-Oriented Systems
Master Java from basic control flow to robust OOP, Collections Framework (ArrayList, HashMap), Exception Handling, File I/O, and Multithreading fundamentals.
Data Analytics Combo (Python + SQL + Excel + Power BI)
The flagship, comprehensive all-in-one data career program. Master Python data science, advanced SQL querying, Excel financial modeling, Power BI business intelligence, and foundational predictive machine learning.
Machine Learning — Basic
Learn foundational machine learning workflows. Covers data preprocessing with Scikit-Learn, linear/logistic regression, decision trees, KNN, evaluation metrics (ROC-AUC, F1), and K-Means clustering.
Machine Learning — Advanced
Master advanced ML and deep learning techniques. Covers Random Forests, XGBoost, LightGBM, PCA, Neural Networks with Keras/TensorFlow, SMOTE for imbalanced data, and FastAPI model deployment.
AI Fundamentals
A comprehensive journey through artificial intelligence concepts. Covers classical state-space search (A*), NLP fundamentals, computer vision with OpenCV, Hugging Face transformers, and AI ethics.
Generative AI (GenAI) — Architectures & RAG
Learn modern Generative AI, Large Language Models (LLMs), prompt engineering, structured JSON outputs, OpenAI/Gemini API integration, and Retrieval-Augmented Generation (RAG) with Vector Databases.