Machine Learning Courses and Certifications

Data Science: Supervised Machine Learning in Python

3555 ratings at Udemy

Full Guide to Implementing Classic Machine Learning Algorithms in Python and with Scikit-Learn

• Udemy
• 6 hours 25 minutes
• Self-Paced
• Paid Course

Feature Engineering for Machine Learning

3492 ratings at Udemy

Learn imputation, variable encoding, discretization, feature extraction, how to work with datetime, outliers, and more.

• Udemy
• 13 hours 24 minutes
• Self-Paced
• Paid Course

Career Certificate

Mathematics for Machine Learning

15100 ratings at Coursera

Build the mathematics behind machine learning: vectors and matrices in linear algebra, multivariate calculus for fitting functions to data, and PCA for compressing high-dimensional data.

• Coursera
• 4 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 3 courses

Introduction to Machine Learning: Supervised Learning

55 ratings at Coursera

Learn to build and evaluate supervised models in Python: linear and logistic regression, k-nearest neighbors, cross-validation, Ridge and Lasso, decision trees, and ensembles.

• Coursera
• 5 weeks, 5 hours a week
• Self-Paced
• Paid Course

Time Series Analysis, Forecasting, and Machine Learning

3148 ratings at Udemy

Python for LSTMs, ARIMA, Deep Learning, AI, Support Vector Regression, +More Applied to Time Series Forecasting

• Udemy
• 23 hours 28 minutes
• Self-Paced
• Paid Course

Great Learning

Coronavirus Outbreak Prediction Using Machine Learning in Hindi

पायथन और मशीन लर्निंग से COVID-19 मामलों व मौतों का विश्लेषण करें और राज्यवार मामलों के आधार पर संक्रमण का पूर्वानुमान लगाएँ।

• YouTube
• 1 hour 4 minutes
• Self-Paced
• Free Video

Master statistics & machine learning: intuition, math, code

3060 ratings at Udemy

A rigorous and engaging deep-dive into statistics and machine-learning, with hands-on applications in Python and MATLAB.

• Udemy
• 1 day 14 hours 21 minutes
• Self-Paced
• Paid Course

The Ultimate Beginner's Guide to AI and Machine Learning

2747 ratings at Udemy

Understand AI, machine learning and neural networks through clear foundations, examples and practical demonstrations.

• Udemy
• 1 day 12 hours 8 minutes
• Self-Paced
• Paid Course

Machine Learning Capstone

218 ratings at Coursera

Build course recommender systems in Python: extract bag-of-words features, compute cosine similarity, cluster with K-means and PCA, apply KNN and matrix factorization, and deploy via Streamlit.

• Coursera
• 5 weeks, 4 hours a week
• Self-Paced
• Paid Course

Introduction to Machine Learning: Unsupervised Learning

19 ratings at Coursera

Uncover structure in unlabeled data: apply PCA and scree plots, cluster with K-means and dendrograms, and complete missing matrices for recommender systems.

• Coursera
• 5 weeks, 3 hours a week
• Self-Paced
• Paid Course

Ensemble Machine Learning in Python: Random Forest, AdaBoost

2655 ratings at Udemy

Ensemble Methods: Boosting, Bagging, Boostrap, and Statistical Machine Learning for Data Science in Python

• Udemy
• 5 hours 48 minutes
• Self-Paced
• Paid Course

Machine Learning- From Basics to Advanced

2337 ratings at Udemy

A beginners guide to learn Machine Learning (including Hands-on projects - From Basic to Advance Level)

• Udemy
• 6 hours 49 minutes
• Self-Paced
• Paid Course

Digital Marketing Tools: Machine Learning and AI

Apply machine learning and big data AI to marketing: evaluate algorithm performance, explore Hadoop, deep learning and neural networks, and predict customer behavior for segmentation and personalization.

• Coursera
• 3 weeks, 1 hour a week
• Self-Paced
• Paid Course

AI skills: Introduction to Unsupervised, Deep and Reinforcement Learning

Learn the fundamentals and principal AI concepts about clustering, dimensionality reduction, reinforcement learning and deep learning to solve real-life problems.

• edX
• 6 weeks, 4-6 hours a week
• Self-Paced
• Free Online Course (Audit)

Machine Learning for Marketers

Apply supervised and unsupervised learning to marketing: segment customers with CART trees, improve prediction accuracy, and use Principal Components Analysis for positioning and personalization.

• Coursera
• 4 weeks, 5 hours a week
• Self-Paced
• Paid Course