Data Science

This comprehensive program covers a range of topics in Data Science and Generative AI. It begins with Core Python Programming Subjective and MCQ Assessments, ensuring a solid foundation in Python, the primary language for data science. Next, learners take a Data Science Fundamentals MCQ Preassessment to gauge their understanding of essential data science concepts and techniques.

Guided Project activities follow, focusing on Data Preprocessing and Exploratory Data Analysis (EDA) to develop skills in handling and analyzing data. Learners then transition to Guided Project activities for Machine Learning, where they learn to build and evaluate predictive models using popular frameworks like Scikit-Learn and TensorFlow.

The program further advances with Guided Project activities centered on Generative AI, where learners explore techniques like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders) to create models that generate new data. Subjective assessments on Machine Learning and Generative AI evaluate the learners' knowledge after completing the guided projects.

Machine Learning using KNN, Random Forest and Decision Tree Algorithm

ML using Python with Scikit-learn and MNIST dataset

Machine Learning using Decision Tree Algorithm

Machine Learning using Linear Regression Model Algorithm