AI & Machine Learning Program (Online)

Service Description

This program offers a deep dive into the foundational principles and advanced methodologies of AI and Machine Learning Algorithms. Students will engage and learn the full machine learning lifecycle, from Data analytics and preprocessing to model development with identifying the ways to evaluate a model. The curriculum is designed to provide hands-on experience with industry-standard tools, fostering a robust understanding of both theoretical concepts and practical implementation. A key focus is on learning the breadth of the applied AI field, its state-of-the-art applications, including the rapidly evolving field of generative AI. Teaching Format: Synchronous Online via Google Meet (Students are expected to have a laptop with internet access and video feature being enabled.) Learning Objectives By the end of this program, students will be able to: 1. Understand and apply the concepts in AI and Machine Learning 2. Prepare and analyze datasets using Python libraries such as Pandas and NumPy to perform feature engineering, data cleaning, and statistical analysis. 3. Build and evaluate supervised, unsupervised and simple Reinforcement Learning models. Implement basic neural networks for classification tasks 4. Learn the concepts of computer vision problems & work on building simple ML Models 5. Explore and use generative AI tools responsibly by Understanding ethical considerations in AI development. 6. Articulate and defend project outcomes by presenting a portfolio of machine learning solutions, demonstrating a mastery of the core concepts to a technical audience. Prerequisites 1. Basic programming experience (Python preferred): While we prefer students have prior experience with Python or Java, our curriculum provides additional support for those new to coding. We offer supplemental materials and resources to help beginners get up to speed. 2. A laptop with internet access: Students will need a personal computer to complete assignments and projects. 3. A Google account: We will be using Google Colab for many of our labs, so a Google account is required to access these resources.