If you’re searching for high‑quality training in data science, Udemy offers a wide range of top-rated courses. Whether you’re an absolute beginner or looking to upskill with machine learning or NLP, here are the standout options meticulously selected based on ratings, enrollment, content breadth, and real‑world relevance.
1. Complete Data Science, Machine Learning, Deep Learning & NLP Bootcamp
Instructor: Krishaitech / Krish Naik
Rating: ⭐ ~4.5 (16,000+ reviews)
Duration: 99 hours, 429 lectures
A project-based course covering math, ML, DL & NLP frameworks.
- Pros: Comprehensive end‑to‑end curriculum; strong hands‑on projects; great for aspiring full‑stack data scientists.
- Cons: Long duration; requires dedication; math fundamentals less intensive.
2. Mathematics – Basics to Advanced for Data Science and GenAI
Instructor: Krishaitech / Krish Naik
Rating: ⭐ ~4.6 (2,400+ reviews)
Duration: 23 hours, 97 lectures
Focused on linear algebra, statistics, probability, and calculus for data science.
- Pros: Excellent preparation for ML/DL; clear explanations of common formulas; ideal for strengthening quantitative foundations.
- Cons: No code/ML projects; best paired with application‑oriented courses.
3. Python for Data Science & Machine Learning Bootcamp
Instructor: Jose Portilla
Rating: ⭐ Highly rated and student‑favorite
This flagship course covers Python basics to ML with scikit‑learn, pandas, NumPy, seaborn, plotly, and real‑world projects.
“Your course is fantastic. It’s one of the absolute best resources for getting started with Python and Data Science.”
- Pros: Clear intro to Python & ML; great for beginners; practical visualization and notebook projects.
- Cons: Less depth in advanced topics like deep learning or NLP; focuses only on Python.
4. Machine Learning A‑Z™: Hands‑On Python & R in Data Science
Instructors: Kirill Eremenko & Hadelin de Ponteves
Rating: ⭐ Very popular among students
Covers Python and R to teach over a dozen ML algorithms with real practice. Great complement to Jose Portilla’s bootcamp.
- Pros: Dual‑language coverage; broad ML algorithm exposure; great if you want R experience.
- Cons: May not suit absolute beginners; math theory not emphasized.
Comparison Table
| Course Title | Best For | Duration | Language |
|---|---|---|---|
| Complete DS, ML, DL & NLP Bootcamp | Full-stack learners | ~99 hrs | Python + frameworks |
| Mathematics Basics to Advanced | Improving math skills for DS/ML | ~23 hrs | Theoretical focus |
| Python for Data Science & ML Bootcamp | Python beginners to ML | ~40–50 hrs | Python |
| Machine Learning A‑Z (Python & R) | Learning algorithms in dual code | ~40 hrs | Python & R |
❓ Frequently Asked Questions
Which course is best for absolute beginners?
Python for Data Science & Machine Learning Bootcamp offers a solid start—straightforward, project-based, and beginner-friendly.
Do I need math before starting?
Not necessarily. But if you want to build a strong foundation, the Mathematics – Basics to Advanced course is highly recommended.
Should I learn both Python and R?
It depends on your goals. Python dominates in data science, but R remains important in academia and finance. Machine Learning A‑Z is perfect if you want exposure to R.
How much time should I expect to invest?
Expect 40–100+ hours depending on the depth of the curriculum. Bootcamps are immersive, while math-specific courses are shorter and focused.
✅ Final Thoughts
- Beginners: Start with Python for Data Science & ML Bootcamp.
- For strong math foundations: Add Mathematics – Basics to Advanced.
- Deep dive: Choose Complete Bootcamp with DL & NLP.
- Diversify: Try Machine Learning A‑Z for Python + R skills.
Pick the combination that matches your learning style and goals—whether that’s building projects, mastering math, or broadening your toolset.