Machine Learning Courses and Certifications logopeterindia.net
Knowledge Hub

Machine Learning Courses and Certifications

Where to learn machine learning in depth and which certifications to take, from maths and algorithms to deep learning and MLOps.

83 topics•9 categories•Updated October 2026

How to Choose a Path

6 entries

Machine learning rewards theory plus practice. Build the maths first (linear algebra, probability, calculus), learn classical ML and then deep learning, implement models in PyTorch or scikit-learn, and finish with MLOps and a cloud ML engineer certification. Pair every course with projects.

01Machine LearningMachine learning hub on this site. 02Machine Learning AlgorithmsSupervised, unsupervised and ensemble methods. 03Machine Learning Frameworksscikit-learn, PyTorch, TensorFlow, JAX and more. 04Deep LearningDeep learning frameworks and datasets. 05MLOps PlatformsTop machine learning operations tools. 06AI/ML CertificationsNine AI and ML exams compared.

Step 1: Maths Foundations

7 entries

Linear algebra, probability and statistics.

07Mathematics for Machine Learning (Coursera)Imperial College specialization on the maths behind ML. 08Khan Academy: linear algebraFree lessons on linear algebra. 09Khan Academy: statistics and probabilityFree lessons on statistics and probability. 103Blue1Brown: neural networksVisual video explanations of neural networks. 11An Introduction to Statistical LearningFree textbook on statistical learning with Python and R. 12Linear AlgebraLinear algebra resources on this site. 13StatisticsStatistics resources on this site.

Step 2: Core Machine Learning Courses

12 entries

Foundational courses from universities and experts.

14Machine Learning Specialization (DeepLearning.AI)Andrew Ng's updated introduction to machine learning. 15Machine Learning (Coursera)Long-running introductory machine learning course. 16Machine Learning Crash Course (Google)Free, self-paced machine learning course from Google. 17Stanford CS229: Machine LearningStanford's graduate machine learning course. 18MIT 6.036: Introduction to Machine LearningFree MIT introduction on OpenCourseWare. 19CMU 10-301/601: Introduction to Machine LearningCarnegie Mellon's introductory course. 20Cornell CS4780: Machine Learning for Intelligent SystemsCornell's course with public lecture notes. 21Probabilistic Machine Learning (Kevin Murphy)Book series on probabilistic machine learning. 22Hands-On Machine Learning notebooksJupyter notebooks that accompany the popular practical book. 23Kaggle LearnShort free lessons and notebooks. 24scikit-learn user guideOfficial guide to the Python ML library. 25NPTELFree university courses from Indian institutes, including machine learning.

Step 3: Deep Learning & Specializations

16 entries

Neural networks, vision, language and multi-task learning.

26Deep Learning Specialization (DeepLearning.AI)Specialization on neural networks, sequence models and more. 27Deep Learning (Coursera)Coursera listing of the deep learning specialization. 28Dive into Deep LearningFree interactive book with code in PyTorch, JAX and TensorFlow. 29Understanding Deep LearningFree textbook on deep learning. 30Deep Learning (Goodfellow, Bengio, Courville)Free online textbook on deep learning. 31fast.ai Practical Deep LearningFree, code-first deep learning course. 32Neural Networks: Zero to Hero (Karpathy)Video series building neural networks and language models from scratch. 33Stanford CS231nDeep learning for computer vision. 34Stanford CS224NNLP with deep learning. 35Stanford CS330Deep multi-task and meta learning. 36PyTorch tutorialsOfficial PyTorch tutorials. 37TensorFlow tutorialsOfficial TensorFlow tutorials. 38Keras getting startedOfficial Keras introduction. 39JAX tutorialsOfficial JAX tutorials. 40Hugging Face LearnFree courses on NLP, LLMs and agents. 41Jay Alammar's blogVisual explanations of transformers and other ML ideas.

Reinforcement Learning

5 entries

Decision-making and agents.

42Stanford CS234: Reinforcement LearningStanford's reinforcement learning course. 43Spinning Up in Deep RL (OpenAI)Educational resource on deep reinforcement learning. 44Hugging Face Deep RL CourseFree course on deep reinforcement learning. 45Reinforcement Learning GuideComplete guide to reinforcement learning on this site. 46Federated Learning GuideComplete guide to federated learning on this site.

MLOps & Production ML

11 entries

Taking models to production.

47Machine Learning in Production (DeepLearning.AI, Coursera)Specialization on deploying and maintaining ML systems. 48MLOps specialization (Duke, Coursera)Specialization on machine learning operations. 49Rules of Machine Learning (Google)Google's best practices for machine learning engineering. 50Managing ML projects (Google)Guide to planning and running ML projects. 51MLOps: continuous delivery and automation pipelines (Google Cloud)Architecture guide to MLOps maturity. 52Made With MLFree course on designing and deploying ML applications. 53The Full Stack (Full Stack Deep Learning)Courses and resources for building ML products. 54ml-ops.orgReference site on MLOps principles. 55MLOps CommunityCommunity for MLOps practitioners. 56MLflow documentationDocumentation for the open-source ML lifecycle platform. 57Kubeflow documentationDocumentation for ML on Kubernetes.

Certifications

12 entries

Role-based credentials from cloud and platform vendors.

58AWS Certified Machine Learning Engineer – AssociateAssociate-level AWS credential for building and operating ML workloads. 59AWS Certified AI PractitionerEntry-level AWS credential on AI and ML concepts. 60Professional Machine Learning Engineer (Google Cloud)Professional-level Google Cloud ML credential. 61Azure Data Scientist AssociateMicrosoft credential for ML on Azure; check the page for its current status. 62Azure AI FundamentalsEntry-level Microsoft AI credential. 63Databricks Certified Machine Learning AssociateDatabricks credential for ML on its platform. 64Databricks Certified Machine Learning ProfessionalAdvanced Databricks ML credential. 65NVIDIA certification programsNVIDIA certification programs including generative AI and AI infrastructure. 66SAS Global CertificationSAS certifications in AI and machine learning. 67AWS Skill BuilderAWS training and exam preparation. 68Microsoft LearnFree learning paths for Azure ML. 69Google Skills (formerly Cloud Skills Boost)Google Cloud learning paths with hands-on labs.

Practice, Papers & Community

9 entries

Keep learning and stay current.

70Kaggle competitionsMachine learning competitions for practice. 71Trending Papers (Hugging Face)Trending machine learning papers with code. 72arXiv: machine learningRecent machine learning preprints. 73NeurIPSTop machine learning conference. 74ICMLInternational Conference on Machine Learning. 75ICLRInternational Conference on Learning Representations. 76DistillArchive of clear, interactive ML articles. 77Machine Learning MasteryPractical machine learning tutorials. 78KDnuggetsData science and ML news and resources.

Related Pages

5 entries

Neighbouring pages on this site.

79AI Courses and CertificationsAI learning guide. 80Data Science Courses and CertificationsData science learning guide. 81Free AI CoursesFree AI courses from top universities. 82Free Resources for Learning LLM Inference EngineeringFree path for LLM inference. 83Courses and CertificationsHub for all courses and certifications.

Frequently Asked Questions

How do I learn machine learning?

Build the maths, then work through a core course such as Stanford CS229 or the Machine Learning Specialization, implement models in scikit-learn and PyTorch, and practise on Kaggle.

What is the best machine learning certification?

It depends on your platform. AWS Certified Machine Learning Engineer Associate, Google Professional Machine Learning Engineer and the Databricks ML credentials are the main engineer-level options. Projects and a portfolio carry equal weight.

What maths do I need?

Linear algebra, probability and statistics, and basic calculus. Khan Academy, 3Blue1Brown and the free textbooks listed here cover them.

How is this different from the Data Science and AI guides?

This guide focuses on machine learning theory, deep learning, reinforcement learning and MLOps. The Data Science guide covers analytics and statistics, and the AI guide covers generative AI and AI tools.

How current is this page?

Links were checked in October 2026. Course editions, exam names and prices change often, so confirm details on each provider's own page. Descriptions summarize each provider's pages, and listing is not an endorsement. Some certifications that were once popular (such as TensorFlow Developer) may be retired, so check any credential before preparing for it. Sites that block automated checks are kept and may need a manual click.