If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start. This Specialization, created in partnership between DeepLearning.AI and Stanford University, is an updated and expanded version of Andrew’s original course, one of Coursera’s most popular courses that was taken by nearly 5 million learners.
About Machine Learning Specialization by Andrew Ng
This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field. It summarizes the advances made over the ten years since the original course was released and includes:
- Graded assignments and lectures that teach Python instead of Octave/Matlab
- 3 in-depth courses providing a broad introduction to machine learning, supervised learning, and unsupervised learning
- Dozens of additional code notebooks and interactive graphs to help learners better understand concepts
Is the Machine Learning Specialization worth it?
Yes. By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start. Specifically, you’ll be able to
- build ML models, build & train supervised models for prediction & binary classification tasks,
- build & train a neural network with TensorFlow,
- apply best practices for ML development & use unsupervised learning techniques for unsupervised learning including clustering & anomaly detection
- build recommender systems
Machine Learning Specialization details
- Institutions: DeepLearning.AI and Stanford University
- Provider: Coursera
- Duration: 2 months
- Level: Beginner
- Cost: $49/month
- Language: English
- Certificate: Sharable certificate