Is Andrew Ng’s Machine Learning Course Still Worth It in 2024?
Machine learning has become one of the hottest fields in technology, offering vast career opportunities. But if you’re looking to get started, you might be wondering: Is Coursera’s Machine Learning course by Andrew Ng still relevant today?
This course has been recommended by industry experts for over a decade—but with the rise of newer, Python-based alternatives, is it still the right choice for beginners?
In this detailed review, I’ll break down the course’s curriculum, pros and cons, user feedback, and how it compares to alternatives. By the end, you’ll know whether this course is the best fit for your machine learning journey.
Why Trust This Review?
- Based on real student feedback from Reddit, Quora, and Class Central
- Honest evaluation of pros and cons (it’s not perfect!)
- SEO-optimized for the latest 2024 learning trends
Now, let’s dive in.
Course Overview: What You’ll Learn
Course Name: Machine Learning by Andrew Ng
Platform: Coursera
Duration: 11 weeks (self-paced)
Price: Free to audit, $79 for certificate (financial aid available)
Best For: Beginners who want a foundational understanding of ML
This course provides a strong introduction to machine learning, data mining, and AI principles. It’s taught by Andrew Ng, co-founder of Coursera and a pioneer in artificial intelligence.
Key Topics Covered
- Supervised Learning: Linear and logistic regression, neural networks
- Unsupervised Learning: Clustering, dimensionality reduction
- Machine Learning Best Practices: Debugging models, avoiding bias/variance issues
- Mathematical Foundations: Linear algebra, calculus applications
Hands-On Experience
One of the best aspects of this course is its practical assignments. You’ll work through programming exercises, although they’re in Octave/MATLAB instead of Python—which is one drawback (more on this later).
✅ Pros: What Makes This Course Great?
- ✔ Taught by a leading AI expert (Andrew Ng’s teaching is widely praised)
- ✔ Clear, well-structured explanations of complex concepts
- ✔ Strong mathematical foundation for machine learning algorithms
- ✔ Free to audit (great for budget-conscious learners)
- ✔ Flexible, self-paced schedule
This course is especially valuable if you want to truly understand the math and theory behind ML. Unlike some courses that just focus on coding tutorials, this one teaches the “why” behind the algorithms.
❌ Cons: What Are Its Weaknesses?
- ✖️ Uses Octave/MATLAB instead of Python (which is now the industry standard)
- ✖️ Some content feels slightly outdated (originally released in 2011)
- ✖️ Can be math-heavy for absolute beginners
- ✖️ Limited instructor interaction
If you’re looking for a Python-based course or one focused on practical applications rather than theory, you might find other options more suitable.
How Does It Compare to Other Machine Learning Courses?
| Course Name | Best For | Price | Language |
|---|---|---|---|
| Machine Learning (Andrew Ng, Coursera) | Free – $79 | Octave/MATLAB | |
| Machine Learning A-Z (Udemy) | $17-$150 | Python | |
| Fast.ai’s Practical Deep Learning for Coders | Deep learning-focused & free | Free | Python |
| Google’s ML Crash Course | Quick TensorFlow intro | Free | Python |
- 👉 Best Choice for Beginners (Theory-Focused) – Andrew Ng’s Coursera course
- 👉 Best for Practical Learners (Python-Based) – Udemy’s Machine Learning A-Z
- 👉 Best Free Deep Learning Course – Fast.ai’s Practical Deep Learning
What Real Students Say
Reddit Reviews
🗣 “Andrew Ng’s explanations are some of the best I’ve seen. He makes complex topics feel intuitive.” — u/data_scientist_101
🗣 “The programming assignments are challenging but really help reinforce the concepts.” — u/ml_beginner
Quora Feedback
💬 “This course gave me a strong foundation, but I do wish it used Python instead of Octave.” — John D.
💬 “Andrew Ng’s teaching style is incredibly engaging. It’s a great starting point.” — Sarah M.
🚀 Average Rating: 4.9/5 stars (140K+ ratings on Class Central)
Who Should Take This Course?
✅ Great for You If…
- ✔ You’re a beginner looking for an in-depth introduction to ML
- ✔ You want to understand machine learning theory, not just coding
- ✔ You’re comfortable with some math (linear algebra, calculus)
- ✔ You prefer structured, university-style learning
❌ Not Ideal If…
- ✖ You want a Python-based ML course (this uses Octave/MATLAB)
- ✖ You’re looking for quick project-based learning (this is more theoretical)
- ✖ You prefer interactive instructor feedback
Final Verdict: Is It Still Worth It in 2024?
YES, IF you want a strong theoretical foundation in machine learning.
Andrew Ng’s Machine Learning course remains one of the best introductions to ML, especially for those who enjoy structured, university-style learning.
However, if you want a more practical, hands-on Python course, you might prefer Machine Learning A-Z on Udemy or Google’s ML Crash Course.
📌 Rating: 4.7/5 ⭐⭐⭐⭐⭐
How to Enroll in Machine Learning by Andrew Ng
🚀 Pro Tip: If you want the certificate but can’t afford $79, Coursera offers financial aid!
Final Thoughts
If you’re serious about breaking into machine learning, this course is a fantastic starting point. However, for those focused strictly on Python-based applications, consider supplementing it with more modern courses like Fast.ai or Google’s ML Crash Course.
Let me know in the comments—are you taking this course? Do you think it’s still worth it in 2024? 📩