Live Online AI Course for Professionals

This live online course is tailored for professionals aiming to break into the world of Artificial Intelligence or advance their current roles with AI expertise. It begins with foundational AI concepts and quickly progresses into practical applications using Python. Learners will explore supervised and unsupervised machine learning, deep learning fundamentals, and model evaluation techniques. The course also dives into real-world use cases involving computer vision, NLP, and AI ethics. Through projects and case studies, learners will build AI solutions such as chatbots, image classifiers, and recommendation systems—bridging theory and practice to prepare for roles in AI development, data science, and automation.

Key Benefits:

• Taught by industry experts with real-world experience
• Combines theory with hands-on coding and case studies
• Covers end-to-end pipeline: data preprocessing to model deployment
• Ideal for upskilling or transitioning into AI-focused roles
• Access to career-oriented projects and certification

What You’ll Learn:

AI Foundations

• What is AI? History, applications, types of AI

• Overview of machine learning, deep learning, and neural networks

• Setting up Python environment for AI development

Machine Learning Essentials

• Supervised learning: regression, classification

• Unsupervised learning: clustering, dimensionality reduction

• Model training, testing, tuning (train/test split, cross-validation)

• Feature engineering and selection

Deep Learning & Neural Networks

• Basics of neural networks and backpropagation

• Building deep learning models using TensorFlow/Keras

• CNNs for image processing

• RNNs and LSTMs for sequential data

AI Applications

• Natural Language Processing (NLP): text classification, sentiment analysis

• Computer Vision: object detection, facial recognition

• Building AI-powered applications: chatbots, recommenders

Advanced Topics

• Model deployment and APIs

• Explainable AI (XAI)

• AI ethics, bias in algorithms, responsible AI development