Advanced Artificial Intelligence (AI) – Self Paced

Take your AI skills to the next level with our “Advanced Artificial Intelligence” course, carefully designed as per AICTE norms to meet academic and industry standards. This self-paced IBM-certified program is ideal for learners who already understand the basics of AI and want to explore advanced techniques in Deep Learning, Natural Language Processing (NLP), Computer Vision, Reinforcement Learning, Bayesian Learning, and cutting-edge AI applications.

This course offers a comprehensive learning journey that starts with the foundations of Artificial Intelligence and expands into real-world applications such as speech recognition, autonomous systems, fraud detection, biomedical AI, recommendation systems, and social media sentiment analysis. You will also explore the ethics and governance of AI, preparing you for both technical expertise and responsible AI practice.

📖 Course Modules

1. Introduction to Artificial Intelligence

• What is AI? Key concepts and definitions

• Applications of AI: Robotics, NLP, Computer Vision, etc.

• History and Evolution of AI: Timeline of key milestones

• Ethical & Social Issues: Privacy, bias, job displacement

2. Programming for AI

• Python programming concepts for AI

• Deep learning frameworks: TensorFlow & PyTorch

• Data preprocessing, cleaning, and handling missing values

3. Machine Learning

• Supervised Learning: Ensemble methods, SVMs, Gradient Boosting

• Unsupervised Learning: Clustering, Autoencoders, GANs

• Reinforcement Learning: Q-Learning, Policy Learning, Markov models

4. Natural Language Processing (NLP)

• Word embeddings, CNNs & RNNs for text classification & sentiment analysis

• Named Entity Recognition (NER) & Information Extraction

• Text Summarization & Generation with deep learning models

5. Speech Recognition

• Techniques and real-world applications

6. Computer Vision

• Object detection: YOLO, Faster R-CNN, Mask R-CNN

• Image segmentation: Semantic & Instance segmentation

• Deep Learning for video analysis: Action recognition & object tracking

7. Advanced Deep Learning Topics

• CNNs, RNNs, Attention Mechanisms

• Transfer Learning & Domain Adaptation

8. Deep Reinforcement Learning

• Advanced reinforcement learning models

9. Bayesian Learning & Probabilistic Models

• Bayesian Learning introduction

• Bayesian Networks & Hidden Markov Models

10. Advanced Applications of AI

• Autonomous systems: self-driving cars, drones

• AI in Cybersecurity & Fraud Detection

• Biomedical AI: medical imaging, drug discovery, personalized medicine

• Recommendation Systems & Social Media Sentiment Analysis

11. AI and Society

• Ethics & Governance of AI

• Impact of AI on economy & future of work

🌟 Why Choose This Course?

• AICTE-aligned syllabus for academic & industry relevance

• Learn advanced AI, ML, NLP, and Computer Vision concepts

• Hands-on with TensorFlow, PyTorch, NumPy, and Pandas

• Future-ready skills for high-demand AI careers

• Self-paced learning from IBM-certified instructors

By the end of this course, you will gain deep knowledge of AI algorithms, frameworks, and advanced applications, making you industry-ready for roles in AI development, Machine Learning engineering, Data Science, and Research.