Move beyond college textbook theory. Master normalized relational databases, scalable FastAPI backends, Docker containers, and end-to-end data analytics pipelines.
BTech (CSE/IT/ECE), BCA, BSc CS, and MCA students in 1st to 4th year
12 WeeksMaster 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.
6 WeeksMaster Microsoft Excel from essential formulas and conditional formatting to modern XLOOKUP, pivot tables, data cleaning, and dynamic executive dashboards.
6 WeeksTransform raw data into compelling interactive business intelligence reports. Learn Power Query ETL, Star Schema data modeling, DAX measures, time intelligence, and cloud publishing.
6 WeeksMaster relational databases, complex multi-table joins, subqueries, CTEs, analytical window functions, transactions, and normalized schema design using PostgreSQL and MySQL.
4 WeeksLearn document databases from the ground up. Covers MongoDB Atlas, CRUD operations, Aggregation Pipelines ($match, $group, $lookup), schema design patterns, and indexing for high performance.
8 WeeksMaster low-level programming, computer memory architecture, pointers, dynamic memory allocation (malloc/free), structs, and file I/O.
8 WeeksMaster Modern C++, Object-Oriented paradigms (Inheritance, Polymorphism, Abstraction), Standard Template Library (Vectors, Maps, Sets, Algorithms), and generic Templates.
8 WeeksMaster Java from basic control flow to robust OOP, Collections Framework (ArrayList, HashMap), Exception Handling, File I/O, and Multithreading fundamentals.
14 WeeksThe 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.
8 WeeksLearn 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.
8 WeeksMaster 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.
6 WeeksA comprehensive journey through artificial intelligence concepts. Covers classical state-space search (A*), NLP fundamentals, computer vision with OpenCV, Hugging Face transformers, and AI ethics.
6 WeeksLearn modern Generative AI, Large Language Models (LLMs), prompt engineering, structured JSON outputs, OpenAI/Gemini API integration, and Retrieval-Augmented Generation (RAG) with Vector Databases.