Artificial Intelligent - Internship Syllabus

Kickstart your career in AI with our hands-on Artificial Intelligence Internship Program designed for students, graduates, and working professionals. This program provides you with real-world projects, expert mentorship, and industry exposure to prepare you for a future in AI, Machine Learning, and Data Science.

📘 Course Modules

1. Definition & history of AI
2. Applications of AI
3. Turing Test & Rational Agent
4. Foundations of AI
5. Types of AI (Narrow, General, Super AI)
6. Intelligent Agents
7. Problem formulation
8. State space search
9. Search strategies
10. Heuristics & evaluation functions
11. Constraint Satisfaction Problems (CSPs)
12. Propositional & Predicate Logic
13. Knowledge-based agents
14. Inference in logic
15. Forward & backward chaining
16. Resolution
17. Ontologies and semantic networks
18. Frames and scripts
19. Non-monotonic reasoning & default reasoning
20. Planning problem
21. Classical planning
22. Partial-order planning
23. Conditional & hierarchical planning
24. Multi-agent planning
25. Supervised, Unsupervised & Reinforcement Learning
26. Decision trees
27. Naive Bayes
28. k-Nearest Neighbors (kNN)
29. Neural Networks (basic concepts)
30. Overfitting, underfitting
31. Cross-validation
32. Bayesian Networks
33. Markov Models
34. Hidden Markov Models (HMMs)
35. Inference in probabilistic models
36. Decision theory
37. Text preprocessing
38. Syntax & parsing
39. Semantics
40. POS tagging
41. Named Entity Recognition
42. Sentiment Analysis
43. Chatbots & Dialogue Systems
44. Perception and sensors
45. Robot motion & control
46. Localization & mapping (SLAM)
47. Path planning (A*, D*, RRT)
48. Robot learning
49. Perceptrons & MLPs
50. Backpropagation
51. Convolutional Neural Networks (CNNs)
52. Recurrent Neural Networks (RNNs)
53. Transformers (overview)
54. AI bias & fairness
55. Privacy and surveillance
56. Explainable AI (XAI)
57. AI in society
58. AI alignment and control
59. Future trends