Learn Python, Math, Machine Learning, Build Real-World Projects & Deploy ML Apps on AWS
Sub Category
- Other IT & Software
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Objectives
- Build machine learning models using Python, covering classification, regression, and unsupervised learning.
- Understand the math behind machine learning, including linear algebra, statistics, probability, and calculus with clear intuition.
- Perform data collection, EDA, preprocessing, feature engineering, and model evaluation using real-world datasets.
- Apply cross-validation, hyperparameter tuning, and model selection to build reliable and optimized ML models.
- Convert ML notebooks into production-ready Python scripts and serve models using FastAPI and Streamlit.
- Deploy complete, end-to-end machine learning applications on AWS EC2 with real-world workflows.
Pre Requisites
- No prior Machine Learning experience is required. You will learn everything from scratch.
- No advanced math background is needed. All required math concepts are explained with intuition and examples.
- Basic computer skills and willingness to learn and practice are sufficient.
- A laptop or desktop with internet access (Windows, macOS, or Linux).
- No paid software required. All tools used are free and open-source.
- Some sections involve AWS deployment. An AWS account is helpful but optional.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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