AI & Machine Learning Professional

This course is a hands-on program that teaches you how artificial intelligence systems are built, trained, and deployed in real-world environments.

It starts with the fundamentals of machine learning, where you learn the core concepts behind how models learn from data. You work with practical tools like NumPy and Pandas and build real projects such as price prediction models, fraud detection systems, and customer churn analysis. This gives you a solid foundation in regression, classification, data preprocessing, model training, and evaluation.

In the second module, the focus shifts to deep learning and computer vision. You learn how neural networks — especially Convolutional Neural Networks (CNNs) — are used to analyze images. Through real-world projects like driver distraction detection and plant disease classification, you build, improve, and optimize deep learning models using TensorFlow or PyTorch. You also learn how to deploy these models to the cloud using platforms like AWS or Google Cloud.

The course concludes with a capstone project where you apply everything you’ve learned to build an autonomous self-driving car system in a simulator. This final project ties together machine learning, deep learning, and real-time decision-making.

In summary, this course is about moving from understanding basic machine learning concepts to building and deploying advanced AI systems through practical, project-based learning.

This course includes 10 teacher live-led lessons and a FutureSpex Academy Certification of Attendance.