Oxford University , Harvard University & MIT University , are offering FREE courses👇Here / Or Manor
Oxford University
1. Machine Learning Course
- Understand machine learning's role and evolution.
- Learn about supervised, unsupervised, and reinforcement learning.
- Gain hands-on experience with ML models.
2. What is Generative Artificial Intelligence?
- Explore the importance and concepts of generative AI.
- Learn about GANs, VAEs, and autoregressive models.
- Discover applications in various industries.
https://www.oxfordhomestudy.com/courses/ai-courses-online/what-is-generative-artificial-intelligence
3. Deep Learning
- Understand deep learning history and concepts.
- Learn about neural networks and backpropagation.
- Explore CNNs, RNNs, and NLP applications.
4. What Is Midjourney AI?
- Learn about Midjourney AI's significance and history.
- Understand the models and techniques used.
- Gain insights into AI-generated content creation.
5. What is OpenAI?
- Understand OpenAI's mission and contributions.
- Explore key research areas like NLP and robotics.
- Learn about OpenAI's ethical principles and impact.
6. Stable Diffusions
- Learn about stable diffusions in AI and mathematics.
- Explore diffusion model applications and techniques.
- Gain practical skills in diffusion model analysis.
7. Dall-E Course
- Understand DALL-E's development and architecture.
- Learn how it converts text inputs to visual outputs.
- Explore practical applications in creative industries.
8. AI Claude
- Learn about AI Claude's origins and architecture.
- Explore its applications in diverse sectors.
- Understand principles like NLP and ethical AI.
9. AI General Intelligence
- Understand AGI vs. narrow AI and current progress.
- Explore research approaches to achieving AGI.
- Learn about cognitive science principles in AGI.
10. Online Chat with AI
- Explore AI's role in chat systems and communication.
- Learn about NLP and UX design in chatbot development.
- Discover tools for developing AI chat systems.
Harvard University
1. Introduction to AI with Python.
Learn machine learning in Python.
You will learn:
• Machine learning
• Neural networks
• representation of knowledge
• natural language processing
• And much more.
2. Introduction to Computer Science
Explore computer science and programming.
You will learn:
- Algorithmic thinking
- Project development
- Various languages (C, Python, SQL, etc.)
3. Artificial Intelligence in Business: Creating Value with Machine Learning
→ Learn how to manage AI in companies.
→ Understand when to adopt new technology and align it with business
strategy.
4. Mobile App Development Course
Develop cross-platform native apps using JavaScript with React Native.
Learn:
- JavaScript
- Debugging
- Components, props, state, styling
- Components, views, user input
- And much more.
5. Data Science : Machine Learning
Create a movie recommendation system using data science techniques
Objectives : machine learning basics, cross-validation, key algorithms, recommender systems, regularization
6. CS50's Introduction to Programming with Python
Explore programming using Python for various applications such as:
- Data Science
- Web Programming
- General-Purpose Programming
7. IT for professionals.
You will learn:
→ Programming languages
→ Computational thinking
→ Internet Technologies
→ Web development
→ Technology stacks
→ Cloud computing.
8. Web Programming with Python and JavaScript 2023
A deep dive into web applications using Python and JavaScript.
Learning Objectives: Design and implement web applications, mastery of frameworks.
9. Introduction to Game Development CS50.
Explore 2D and 3D game development, including popular games like Super
Mario Bros., Pokémon, and Angry Birds.
Learn to design and build interactive games.
10. Introduction to Data Science with Python
In this online course, you will learn how to use Python to extract and analyze data.
Learning Objectives:
→ Use popular libraries
→ Run basic ML models
→ Practice using Python for modeling
MIT University
1. Computer Science and Programming Using Python
Topics covered:
→ Notion of computation
→ The Python programming language
→ Some simple algorithms
→ Testing and debugging and more
2. Machine Learning with Python
An in-depth introduction to the field of machine learning.
Topics covered:
→ Principles behind machine learning
→ Implement and analyze models
→ Organizing machine learning projects
3. Becoming an Entrepreneur
Topics covered:
→ Identifying business opportunities
→ Overcoming the top myths of entrepreneurship
→ Defining your goals as an entrepreneur and startup
→ Designing and testing your offering and more
4. Understanding the World Through Data
Become a data explorer – leverage data and machine learning to understand the world.
Topics:
→ Recognizing how data is distributed
→ Dependent and independent variables
→ Observing noise in distributions
5. Foundations of Modern Finance
Topics covered:
→ Financial decisions of households and corporations
→ Approaches to valuing financial and real assets
→ The role and the overview of financial markets
→ Financial Friction and more
6. Data Analysis: Statistical Modeling
A hands-on introduction to the interplay between statistics and computation for the analysis of real data.
Learn models, form hypotheses, perform statistical analysis on real data
7. Entrepreneurship 101
Entrepreneurship can be learned. Begin your journey by learning the first important skill for aspiring entrepreneurs.
Topics covered:
→ Primary customer research
→ Bottom-up market analysis
→ Market segmentation
8. 9. Entrepreneurship 102
Learn and apply the process of entrepreneurial product design.
Topics covered:
→ Analyzing a full product life cycle use case
→ Designing high-level product specifications
→ Estimating quantified value propositions
Enjoy
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