1st lesson free
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Amirhossein
- Rate 229 GHS
- Response 1h
229 GHS/hr
Contact
1st lesson free
- Computer programming
- Python
- Java
- Artificial Intelligence
Practical and up-to-date AI and ML lessons (Master Degree in AI and ML)
- Computer programming
- Python
- Java
- Artificial Intelligence
Lesson location
About Amirhossein
I am an experienced AI and Machine Learning specialist with a strong academic background and extensive hands-on expertise in cutting-edge technologies. Holding a Bachelor’s degree in Computer Science and a Master's degree from Queen Mary University of London, I have worked on a variety of AI, ML, and data science projects that bridge the gap between theory and real-world applications. With a deep passion for teaching and mentoring, I have conducted AI and ML workshops, programming classes, and private tutoring sessions, helping students and professionals gain practical, industry-relevant skills. My approach is highly interactive, project-based, and application-driven, ensuring that students not only understand key concepts but can also implement and optimise AI models effectively. Beyond my technical background, I have a keen interest in music composition and performance, which fuels my creativity and innovative problem-solving approach in AI and ML. I am fluent in Persian, English, and Turkish, making my lessons accessible to a diverse group of learners. Join me to master AI and Machine Learning, explore advanced techniques, and develop real-world projects that will set you apart in the tech industry!
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About the lesson
- Primary school
- Junior high school
- SHS 1
- +14
levels :
Primary school
Junior high school
SHS 1
SHS 2
SHS 3
BTS
Adult Education
Facultate (Licență)
Master's degree
Higher national diploma
Doctor of philosophy
MBA
Beginner
Intermediate
Advanced
Professionel
Child
- English
- Turkish
All languages in which the lesson is available :
English
Turkish
This comprehensive AI and Machine Learning course is designed to provide hands-on experience with real-world applications, focusing on fundamental and advanced topics. The curriculum spans essential machine learning techniques, neural networks, generative models (GANs, VAEs, Stable Diffusion), OpenAI API usage, Langchain, advanced prompt engineering, and real-world AI deployments. My Teaching Approach: I believe in an interactive, project-based learning style that ensures students not only understand theoretical concepts but can also implement them in practical scenarios. Each session includes a mix of: Concept Explanation – Covering theoretical foundations with real-world examples. Hands-On Coding – Implementing algorithms and AI models using Python. Project-Based Learning – Working on assignments and a final capstone project to apply learned skills. Discussion & Q&A – Encouraging students to ask questions and engage in problem-solving discussions. Course Structure & Lesson Format: Sessions: 12 Sessions, each 1 hour long Total Coverage: Machine Learning, Deep Learning, OpenAI API, Langchain, and Prompt Engineering Project-Based Learning: A final capstone project integrating AI techniques and tools Topics Covered: Session 1: Introduction to Machine Learning Core ML concepts, evaluation techniques, and model validation Session 2: Regression Techniques and Regularisation Linear and logistic regression Ridge, Lasso, and Elastic Net regularisation Session 3: Advanced Classification Models Decision Trees, Random Forests, and Boosting techniques Session 4: Neural Networks Fundamentals Basics of neural networks, activation functions, and optimisation Session 5: CNNs, RNNs, and Transformers Convolutional Neural Networks (CNNs) for image tasks Recurrent Neural Networks (RNNs) and Transformers for sequence data Session 6: Generative Models – GANs and VAEs Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) Session 7: OpenAI API Fundamentals OpenAI API, authentication, and integration for AI applications Session 8: Langchain for AI Automation Implementing Langchain for Retrieval-Augmented Generation (RAG) tasks Session 9: Advanced Prompt Engineering Chain-of-Thought (CoT) and Tree-of-Thought (ToT) techniques for AI tasks Session 10: Few-Shot Prompting and Fine-Tuning Developing structured prompts and fine-tuning for specific use cases Session 11: LLaMA Model Integration Comparing OpenAI and LLaMA models for NLP applications Session 12: AI Deployment and Real-World Applications AI model deployment strategies and ethical AI considerations Who Is This Course For? This course is designed for students and professionals who have a basic understanding of Python and want to build strong AI/ML skills. Whether you are an aspiring data scientist, ML engineer, or AI enthusiast, this course will equip you with industry-relevant expertise. Why Learn With Me? Real-World Experience: I hold a Master’s degree from Queen Mary University of London and have worked on multiple AI and ML projects. Hands-On Training: Practical implementation is a key focus, ensuring a deep understanding. Personalised Guidance: I tailor my teaching to each student’s learning pace and interests. Join me on this journey to mastering AI and Machine Learning. Let’s turn theory into practice and build intelligent solutions together!
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Rates
Rate
- 229 GHS
Pack prices
- 5h: 1145 GHS
- 10h: 2290 GHS
online
- GHS229/h
free lessons
The first free lesson with Amirhossein will allow you to get to know each other and clearly specify your needs for your next lessons.
- 1hr
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