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Table of Various AI Training Products
Scroll below to see syllabus of table above. Each Sr. # is described in detail
Syllabus of AI Training
1. Introduction to Artificial Intelligence (AI)
1. Introduction to Artificial Intelligence (AI)
1. Introduction to Artificial Intelligence (AI)
- Program overview
- Magic show to introduce AI
- Definitions of various terms
- Where is AI headed?
2. First Machine Learning (ML) Algorithm
1. Introduction to Artificial Intelligence (AI)
1. Introduction to Artificial Intelligence (AI)
- Simple Linear regression example of ML
- ML workflow
- A real life breast cancer ML project
3. Supervised ML Algorithms
1. Introduction to Artificial Intelligence (AI)
4. Unsupervised ML and Reinforcement Learning
- Review different types of ML algorithms
- Review K Nearest Neighbors algorithm
- Review Decision Tree algorithm
4. Unsupervised ML and Reinforcement Learning
4. Unsupervised ML and Reinforcement Learning
4. Unsupervised ML and Reinforcement Learning
- Review Density Based Scan algorithm
- Introduce Reinforcement learning
5. Introduction to Deep Learning
4. Unsupervised ML and Reinforcement Learning
5. Introduction to Deep Learning
- Introduction to Artificial Neural Network (ANN)
- Architecture of a simple ANN
- Gradient Descent for parameter training
- Steps for training a neural network
6. First Hands on AI project
4. Unsupervised ML and Reinforcement Learning
5. Introduction to Deep Learning
- Introduction to the graphical tool Orange
- Build supervised ML algorithm
- Build unsupervised ML algorithm
7. Introduction to Generative AI and ChatGPT
7. Introduction to Generative AI and ChatGPT
7. Introduction to Generative AI and ChatGPT
- Introduction to GenAI
- The concept of Embeddings
- Lightly cover the functioning of ChatGPT
- Review various GenAI algorithms
- Introduce AI Agents
8. Introduction to Python
7. Introduction to Generative AI and ChatGPT
7. Introduction to Generative AI and ChatGPT
- Installation of Anavonda Navigator
- Introduction to Jupyter Notebooks
- Introduction to Python
- Programming concepts in Python
9. AI/ML Project with Python
7. Introduction to Generative AI and ChatGPT
10. AI guidance for careers other than Computer Science / Engineering
- Review dataset
- Split data in to training and testing set
- Build ML model using training set
- Predict model accuracy using testing set
- Build multiple models
10. AI guidance for careers other than Computer Science / Engineering
10. AI guidance for careers other than Computer Science / Engineering
10. AI guidance for careers other than Computer Science / Engineering
- AI in Healthcare
- AI in Finance & Marketing
- AI in Legal & Journalism
- AI in creative Arts
11. AI Path forward for Students & Professionals
10. AI guidance for careers other than Computer Science / Engineering
11. AI Path forward for Students & Professionals
- Students: Guidance from Ivy league students/alumni
- Professionals: Use case development in your domain
- Executives: AI Vision, Roadmap
- Q&A
12. Test and Certificate of Completion
10. AI guidance for careers other than Computer Science / Engineering
11. AI Path forward for Students & Professionals
- Conduct an online test comprising of multiple choice questions
- A simple programing assignment in No code tool / Python
- Certificate of Completion
Brochure of Students AI Training
Brochure of Professionals AI Training
American AI Tech
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