Machine Learning and Deep Learning Training

The Machine Learning and Deep Learning Training program is an elite, industry-aligned course spanning 3 to 6 months (encompassing 100 to 140+ hours of live instruction and hands-on labs) designed to transition students from foundational programming to advanced artificial intelligence engineering. The comprehensive curriculum bridges traditional statistical modeling with modern neural networks, enabling absolute mastery over an essential tech stack including NumPy, Pandas, Scikit-Learn, PyTorch, and TensorFlow. Beyond theoretical knowledge, the course delivers significant career benefits through portfolio-ready capstone projects—such as object detectors and LLM RAG pipelines—and extensive placement support including ATS resume optimization, mock interviews, and direct corporate hiring drives to ensure high-demand career transitions into MLOps, Computer Vision, or Data Science.

To earn your certification, you will undergo a comprehensive final evaluation structured to measure mathematical concepts, machine learning algorithm selection, neural network architecture design, and hyperparameter tuning. The final assessment carries a 50% grading weightage, with the remaining 50% determined by your continuous lab assignments and capstone project defense. This final certification exam is a timed session lasting 120 to 180 minutes, consisting of multiple-choice questions, multi-select conceptual queries, and practical code-snippet analyses, which can be securely taken either online via remote proctoring or at an authorized testing facility at designated slots at the end of the program.