The following is a list of the top best curated Machine Learning coursera courses that are highly in demand and you can enroll for free.
TOP 18 Machine Learning Courses:
Core Module:
- Neural Networks and Deep Learning
- Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
- Structuring Machine Learning Projects
- Convolutional Neural Networks
- Sequence Models
Offered by: deeplearning.ai
Core Module:
- Introduction
- Linear Regression with One Variable
- Linear Algebra Review
- Linear Regression with multiple Variables
- Octave/Matlab Tutorial
- Logistic Regression
- Regularization
- Neural Networks: Representation
- Neural Networks: Learning
- Advice for Applying Machine Learning
- Machine Learning System Design
- Support Vector Machines
- Unsupervised Learning
- Dimensionality Reduction
- Anomaly Detection
- Recommender Systems
- Large Scale Machine Learning
- Application Examples: Photo OCR
Offered by: Stanford University
3. Mathematics for Machine Learning
Core Module:
- Mathematics for Machine Learning: Linear Algebra
- Mathematics for Machine Learning: Multivariate Calculus
- Mathematics for Machine Learning: PCA
Offered by: Imperial College London
Core Module:
- Introduction to Deep Learning
- How to Win a Data Science Competition: Learn from Top Kagglers
- Bayesian Methods for Machine Learning
- Practical Reinforcement Learning
- Deep Learning in Computer Vision
- Natural Language Processing
- Addressing Large Hadron Collider Challenge by Machine Learning
Offered by: National Research University Higher School of Economics
5. Machine Learning with TensorFlow on Google Cloud Platform
Core Module:
- How Google does Machine Learning
- Launching into Machine Learning
- Intro to TensorFlow
- Feature Engineering
- Art and Science of Machine Learning
Offered by: Google Cloud
6. Machine Learning and Reinforcement Learning in Finance
Core Module:
- Guided Tour of Machine Learning in Finance
- Fundamentals of Machine Learning in Finance
- Reinforcement Learning in Finance
- Overview of Advanced Methods of Reinforcement Learning in Finance
Offered by: NYU | Tandon School of Engineering
7. Probabilistic Graphical Models
Core Module:
- Probabilistic Graphical Models 1: Representation
- Probabilistic Graphical Models 2: Inference
- Probabilistic Graphical Models 3: Learning
Offered by: Stanford University
8. Advanced Data Science with IBM
Core Module:
- Fundamentals of Scalable Data Science
- Advanced Machine Learning and Signal Processing
- Applied AI with Deep Learning
Offered by: IBM
9. Applied Data Science Specialization
Core Module:
- Python for Data Science and Ai
- Data Analysis with Python
- Data Visualization with Python
- Applied Data Science Capstone
Offered by: IBM
10. Data Mining
Core Module:
- Data Visualization
- Text Retrieval and Search Engines
- Text Mining and Analytics
- Pattern Discovery in Data Mining
- Cluster Analysis in Data Mining
- Data Mining Projects
Offered by: Illinois
Core Module:
- Introduction to Recommender Systems: Non-Personalized and Content-Based
- Nearest Neighbor Collaborative Filtering
- Recommender Systems: Evaluation and Metrics
- Matrix Factorization and Advanced Techniques
- Recommender Systems Capstone
Offered by: University of Minnesota
12. Introduction to Machine Learning
Core Module:
- Simple Introduction to Machine Learning
- Basic of Model learning
- Image Analysis with Convolutional Neural Network
- Introduction to Natural Language Processing
- Introduction to Reinforcement Learning
Offered by: Duke University
13. Convolutional Neural Networks in TensorFlow
Core Module:
- Exploring a Larger Dataset
- Augmentation: A Technique to Avoid Overfitting
- Transfer Learning
- Multiclass Classifications
Offered by: deeplearning.ai
14. Computational Neuroscience
Core Module:
- Introduction & Basic Neurobiology
- What do Neurons Encode? Neural Encoding Models
- Extracting Information from Neurons: Neural Decoding
- Information Theory & Neural Coding
- Computing in Carbon
- Computing with Networks
- Networks that Learn: Plasticity in the Brain & Learning
- Learning form Supervision and Rewards
Offered by: University of Washington
15. Machine Learning
Core Module:
- Machine Learning Foundations: A Case Study Approach
- Machine Learning: Regression
- Machine Learning: Classification
- Machine Learning: Clustering and Retrieval
Offered by: University of Washington
16. Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization
Core Module:
- End-to-End Machine Learning with TensorFlow on GCP
- Production Machine Learning Systems
- Image Understanding with TensorFlow on GCP
- Sequence Models for Time Series and Natural Language Processing
- Recommendation Systems with TensorFlow on GCP
Offered by: Google Cloud
17. Sequences, Time Series and Prediction
Core Module:
- Sequences and Prediction
- Deep Neural Networks for Time Series
- Recurrent Neural Networks for Time Series
- Real-World Time Series Data
Offered by: deeplearning.ai
18. Natural Language Processing in TensorFlow
Core Module:
- Sentiment in Text
- Word Embeddings
- Sequence Models
- Sequence Models and Literature
Offered by: deeplearning.ai
Many of the courses that are available in Coursera have the audit option, which allows you to access course materials for free.
Below are steps for you to enroll for a specific course for free:
- Open the Coursera homepage of the course that you wants to Enroll in
- Click on the Enroll for free option button
- Fill in the given subscription form
- In the next screen, click the Start Free Trial button.
- Enter the details of your Credit card or Paypal details
- Start Free Trial button at the bottom of the screen
- You will get a 1-week free trial for the course you want to enroll in
All the best and do let us know if you have any questions.
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