Short AI Course by TTC

The Training Company Courses Terms and Facilities

1. Introduction to Artificial Intelligence
   - Definition and brief history of AI
   - Applications and impact of AI in various fields

2. Problem Solving and Search Algorithms
   - Problem formulation and goal setting
   - Uninformed search algorithms (BFS, DFS)
   - Heuristic search algorithms (A*, Greedy search)
   - Constraint satisfaction problems

3. Knowledge Representation and Reasoning
   - Propositional logic and predicate logic
   - Knowledge representation using semantic networks, frames, and ontologies
   - Inference and deduction using logical reasoning

4. Machine Learning Basics
   - Introduction to machine learning and its types
   - Supervised learning: regression and classification
   - Unsupervised learning: clustering and dimensionality reduction
   - Evaluation and validation of machine learning models

5. Neural Networks and Deep Learning
   - Basics of artificial neural networks
   - Activation functions and gradient descent
   - Deep learning architectures (Convolutional Neural Networks, Recurrent Neural Networks)
   - Training and fine-tuning deep learning models

6. Natural Language Processing
   - Introduction to NLP and its applications
   - Text preprocessing techniques
   - Language modeling and sentiment analysis
   - Named entity recognition and part-of-speech tagging

7. Reinforcement Learning
   - Introduction to reinforcement learning
   - Markov Decision Processes and Q-learning
   - Exploration-exploitation trade-off
   - Deep reinforcement learning and applications

8. AI Ethics and Social Implications
   - Ethical considerations in AI development and deployment
   - Bias and fairness in AI algorithms
   - Privacy and security concerns
   - AI's impact on the job market and society

9. AI in Practice
   - Real-world case studies and applications of AI
   - Industry-specific AI implementations
   - AI project management and deployment considerations

10. Future Trends in AI
    - Cutting-edge developments and research areas in AI
    - Emerging technologies (e.g., explainable AI, quantum computing)
    - The future of AI and its potential challenges and opportunities

What is AI

artificial intelligence

artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience.

What is Machine Learning

https://www.techtarget.com/searchenterpriseai/definition/machine-learning-ML

Big data in AI

https://online.maryville.edu/blog/big-data-is-too-big-without-ai/

Some AI Terms

https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_terminology.htm

What is an AI enabled company ?

https://analyticsindiamag.com/whats-the-difference-between-true-ai-ai-enabled-companies/

https://www.entrepreneur.com/article/381442

What machine learning can and cannot do

https://medium.com/@stefanovskyi/what-machine-learning-can-do-and-what-can-not-difficult-stuff-in-simple-words-ef9f245dd6f6

What is deep learning