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Skillup
- Rate R147
- Response 1h
R147/h
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- Data Analysis
Artificial Intelligence with python expertise & top Institute in India data analytics and data science
- Data Analysis
Lesson location
About Skillup
Course Content Suggestions for AI: 1. Introduction to Artificial Intelligence - History of AI - AI vs. Machine Learning vs. Deep Learning - AI in real-world applications - Ethical considerations in AI 2. Python for AI - Python basics (data structures, functions, object-oriented programming) - Popular libraries for AI (NumPy, pandas, matplotlib) - Jupyter Notebooks and data visualization 3. Machine Learning Fundamentals - Supervised learning (classification, regression) - Unsupervised learning (clustering, dimensionality reduction) - Reinforcement learning basics Evaluation metrics (accuracy, precision, recall, F1-score) 4. Deep Learning Essentials - Neural networks - Convolutional Neural Networks (CNNs) - Recurrent Neural Networks (RNNs) and LSTMs - Autoencoders and Generative Adversarial Networks (GANs) 5. Natural Language Processing (NLP) - Tokenization, stemming, and lemmatization - Sentiment analysis and language models - Word embeddings (Word2Vec, GloVe) - Transformer models and GPT 6. Computer Vision - Image classification and object detection - Image segmentation - Applications of CNNs in vision - Hands-on projects with OpenCV 7. Reinforcement Learning - Q-Learning, SARSA - Deep Q Networks (DQN) - Applications in games, robotics, and automation 8. AI in Robotics - Integrating AI with robotic systems - Simultaneous Localization and Mapping (SLAM) - Reinforcement learning for robotic control 9. AI for Healthcare - AI-based medical diagnostics - Predictive models for disease detection - Case studies on AI in healthcare 10. Capstone Projects - Developing AI models for real-world problems (e.g., product recommendation, autonomous driving, medical applications)
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About the lesson
- Primary
- Secondary
- Matric/GCSE
- +12
levels :
Primary
Secondary
Matric/GCSE
AS Level
A Level
BTech
Adult education
Masters
Doctorate
MBA
Beginner
Intermediate
Advanced
Professional
Kids
- English
Languages in which the lesson is available :
English
Course Content Suggestions for AI:
1. Introduction to Artificial Intelligence
- History of AI
- AI vs. Machine Learning vs. Deep Learning
- AI in real-world applications
- Ethical considerations in AI
2. Python for AI
- Python basics (data structures, functions, object-oriented programming)
- Popular libraries for AI (NumPy, pandas, matplotlib)
- Jupyter Notebooks and data visualization
3. Machine Learning Fundamentals
- Supervised learning (classification, regression)
- Unsupervised learning (clustering, dimensionality reduction)
- Reinforcement learning basics
Evaluation metrics (accuracy, precision, recall, F1-score)
4. Deep Learning Essentials
- Neural networks
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs) and LSTMs
- Autoencoders and Generative Adversarial Networks (GANs)
5. Natural Language Processing (NLP)
- Tokenization, stemming, and lemmatization
- Sentiment analysis and language models
- Word embeddings (Word2Vec, GloVe)
- Transformer models and GPT
6. Computer Vision
- Image classification and object detection
- Image segmentation
- Applications of CNNs in vision
- Hands-on projects with OpenCV
7. Reinforcement Learning
- Q-Learning, SARSA
- Deep Q Networks (DQN)
- Applications in games, robotics, and automation
8. AI in Robotics
- Integrating AI with robotic systems
- Simultaneous Localization and Mapping (SLAM)
- Reinforcement learning for robotic control
9. AI for Healthcare
- AI-based medical diagnostics
- Predictive models for disease detection
- Case studies on AI in healthcare
10. Capstone Projects
- Developing AI models for real-world problems (e.g., product recommendation, autonomous driving, medical applications)
See more
Rates
Rate
- R147
Package rates
- 5h: R735
- 10h: R1470
online
- R147/h
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