Post Graduate Program in AI & Machine Learning

The Mathematics and Statistics Foundations course establishes a strong mathematical and statistical principles base, fostering critical thinking and problem-solving skills. This course equips students with the ability to analyze data, make informed decisions, and apply these techniques to relevant industry scenarios. It serves as an essential starting point for further learning in the program.

This course provides you with essential Python programming skills that will serve as the building blocks for your entire program journey. You will learn how to effectively implement artificial intelligence (AI) and machine learning (ML) algorithms, conduct data analysis, and construct intelligent systems efficiently using Python

Developed by IBM, this course equips students with the skills to leverage Python for data science. By the end of the course, participants will be proficient in writing Python scripts and performing hands-on data analysis using a Jupyter-based lab environment.

This course provides coverage of key concepts in data science, such as data preparation, model development, and evaluation. Throughout the course, you will develop a strong understanding of fundamental Python concepts such as strings, Lambda functions, and lists. You will explore various important skills such as Z-test, T-test, and ANOVA. Furthermore, you will acquire data visualization skills using popular libraries like Matplotlib, Seaborn, Plotly, and Bokeh.

This course comprehensively covers various types of machine learning and their practical applications. You will explore the machine learning pipeline and delve into topics such as supervised learning, regression models, and classification algorithms. You will also study unsupervised learning, including clustering techniques and ensemble modeling. Evaluate machine learning frameworks like TensorFlow and Keras, and build a recommendation engine with PyTorch.

Elevate your machine learning skills to the next level with this comprehensive course on deep learning using TensorFlow and Keras. Gain a thorough understanding of deep learning concepts, empowering you to construct artificial neural networks and navigate through complex data abstraction layers. By harnessing the potential of data, this course prepares you to venture into new frontiers of Artificial Intelligence.

This comprehensive course provides you with the necessary skills to deploy deep learning tools using AI/ML frameworks. You will explore the fundamental concepts and applications of deep learning and understand the distinctions between DL and ML. The course covers a range of topics, including neural networks, forward and backward propagation, TensorFlow 2, Keras, model interpretability, CNNs, transfer learning, object detection,RNNs, autoencoders, and creating neural networks in PyTorch.

This comprehensive course thoroughly explains generative AI models, specifically focusing on ChatGPT. Participants will acquire practical skills to leverage ChatGPT for building and deploying AI chatbot applications effectively. The course covers topics such as generative AI, explainable AI, prompt engineering, fine-tuning, ethical considerations, and the future of generative AI.

The capstone project allows you to implement the skills you learned throughout this bootcamp. You will solve industry-specific challenges by leveraging various AI and ML techniques. The capstone project is the final step in the core learning path and will help you showcase your expertise to employers.