DeepLearning.AI Machine Learning Specialization
Practical machine learning course covering supervised learning, neural networks, and real-world ML practices. Created by Andrew Ng.
Provider
DeepLearning.AI/Coursera
Level
Professional
Duration
2–3 months
Cost
$200
Passing Score
Pass/Fail
Validity
Lifetime
Salary Impact
+$10,000–$20,000 avg
Prerequisites
Python proficiency
Linear algebra basics
Calculus fundamentals helpful
Exam Format
Programming assignments and quizzes, no traditional exam
Exam Topics & Weights
Supervised learning fundamentals
30%
Neural networks and deep learning
35%
Optimization and regularization
20%
Practical ML techniques
15%
8-Week Study Plan
Weeks 1-2
Focus: Supervised learning fundamentals
Linear regression
Logistic regression
Cost functions
Weeks 3-4
Focus: Neural networks from first principles
Forward propagation
Backpropagation
Activation functions
Weeks 5-6
Focus: Deep neural networks and optimization
Multi-layer networks
Gradient descent variants
Hyperparameter tuning
Weeks 7-8
Focus: Practical ML and best practices
Train/val/test splits
Bias-variance tradeoff
ML system design
Exam Tips & Strategies
Andrew Ng's teaching is world-class—pay close attention to intuitions
Programming assignments require Python and NumPy
Focus on understanding math intuitions, not just formulas
Bias-variance tradeoff is fundamental to ML
This specialization is excellent before diving into frameworks like TensorFlow
Build projects to solidify learning
Ready to Apply? Use HireKit's Free Tools
AI-powered job search tools for DeepLearning.AI Machine Learning Specialization
Add to Your Resume
Showcase this certification on an ATS-optimized resume
ATS Resume Checker
Verify your updated resume passes ATS screening
hirekit.co — AI-powered job search platform
Ready to start preparing for DeepLearning.AI Machine Learning Specialization?
Get a personalized study plan and track your progress toward certification.
Start Learning