Timed, domain-weighted mock exams with clear explanations—master AI/ML fundamentals, LLMs, prompting and RAG
Sub Category
- IT Certifications
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Objectives
- Core AI/ML concepts: models, data, training vs inference
- Supervised vs unsupervised learning, regression vs classification
- NLP/CV basics: tokenization, embeddings, image and audio pipelines
- Generative AI & LLMs: decoding, temperature, top-k/top-p
- Prompting skills: clear tasks, few-shot, structured outputs
- Retrieval-Augmented Generation (RAG): vectors, similarity search, reranking
- Evaluation: accuracy, precision/recall, F1, ROC/PR-AUC, drift
- Responsible AI: bias, fairness, privacy, transparency, safety guardrails
- MLOps fundamentals: versioning, deployment, monitoring, canary/shadow tests
- Real-world use cases and hands-on exercises to apply concepts fast
Pre Requisites
- No formal prerequisites—beginners welcome. Recommended: basic computer skills and high-school math (percentages, averages, light algebra). Helpful but not required: basic Python or spreadsheet skills, and familiarity with CSV/JSON. You’ll need a laptop with a modern browser and internet; labs use free, browser-based tools (no heavy installs). Ideal for students, career-switchers, and IT/tech pros seeking a practical intro to AI/ML, LLMs, prompting, RAG, evaluation, and responsible AI. If you’re brand-new, you’ll get step-by-step guidance; if you’re experienced, the practice tasks and quizzes will still challenge you.
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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