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Machine Learning Free Online Course with Certification [2025]

Machine Learning Free Online Course with Certification [2025]

Q: 1. What’s the best way to start learning machine learning if I have no prior experience in AI?

If you’re new to AI, start with foundational courses that cover basic statistics, Python programming, and core ML concepts like supervised and unsupervised learning. Focus on hands-on projects and gradually explore libraries like scikit-learn. Avoid jumping into deep learning too soon; build a solid base first.

Q: 2. How do I choose the right machine learning specialization for my career goals?

Identify whether you want to work in data science, computer vision, NLP, or reinforcement learning. Each has its tools and techniques, so look for courses and projects aligned with your interests. Consider industry demand, your background, and your desired job roles when picking a specialization.

Q: 3. What are the must-have projects to include in my AI portfolio to impress recruiters?

Recruiters look for projects that solve real-world problems with clear objectives and outcomes. Examples include image classification, sentiment analysis, recommendation systems, or time-series forecasting. Make sure your code is clean and documented and that you can confidently explain the model choices and performance metrics.

Q: 4. How necessary is math knowledge in AI, and which topics should I focus on?

Math is essential for understanding how algorithms work under the hood. Focus on linear algebra, probability, statistics, and calculus basics. You don’t need to be a math wizard, but a good grasp will help you debug models and develop custom solutions rather than relying solely on libraries.

Q: 5. Can I learn machine learning effectively without a degree in computer science?

Absolutely. Many successful AI practitioners come from diverse backgrounds. Online courses, bootcamps, and open-source projects can teach you what you need. However, dedication to learning programming and math basics is crucial since those are foundational skills in AI.

Q: 6. How do I stay updated with the latest AI and machine learning advancements?

Follow conferences like NeurIPS, ICML, and CVPR, and read papers from arXiv. Subscribe to newsletters, blogs, and join AI communities on Reddit, LinkedIn, or Stack Overflow. Practical experimentation with new models and frameworks also helps you stay current.

Q: 7. What’s the best way to transition from traditional software development to AI and machine learning roles?

Leverage your programming skills by starting with ML libraries like TensorFlow or PyTorch. Take project-based courses focused on AI workflows. Also, your resume and interviews emphasize your understanding of data preprocessing, feature engineering, and model evaluation.

Q: 8. How do I handle imbalanced datasets in machine learning projects?

Common strategies include resampling techniques like oversampling the minority class or undersampling the majority class, using synthetic data generation (SMOTE), and choosing evaluation metrics such as precision-recall or F1 score over accuracy to measure model performance better.

Q: 9. Which programming languages and tools should I focus on to build a career in AI?

Python is the most popular language for AI due to its rich ecosystem of libraries (scikit-learn, TensorFlow, PyTorch). R is useful for statistics-heavy projects. Familiarize yourself with Jupyter notebooks, version control (Git), and cloud platforms like AWS or Google Cloud for scalable AI solutions.

Q: 10. How important is deep learning compared to classical machine learning techniques?

Deep learning is powerful for tasks involving unstructured data like images, audio, and text, but classical ML methods are still very effective for tabular data and smaller datasets. Understanding both allows you to choose the best approach for a problem rather than defaulting to deep learning.

By Pavan Vadapalli

Updated on May 20, 2025 | 10 min read | 7.52K+ views

Latest Update:

Netflix rakes in a whopping $1 billion every year, all thanks to its machine learning-powered recommendation system? This tech boost not only keeps viewers hooked but also highlights why 61% of marketers say AI and ML are game-changers for their growth strategies. It's clear—businesses everywhere are tapping into the power of machine learning to stay ahead of the competition and deliver ultra-personalized experiences!

Machine Learning is now one of the most popular skills in tech. It’s used in everything from movie recommendations to self-driving cars. If you want to start learning it or improve your skills, a free online course with a certificate is a great way to begin. Plenty of good options don’t cost anything and still offer real value for your career.

In this blog, you’ll discover the best free machine learning courses that offer certificates. You’ll learn what each course covers, where to access them, and how they can help you take the next step in your learning or career journey.

Looking to strengthen your machine learning skills? upGrad’s Artificial Intelligence & Machine Learning - AI ML Courses help you build real-world problem-solving abilities. Learn to design intelligent systems and apply machine learning models in practical scenarios.

To build a strong foundation in machine learning and apply it across real business problems, explore these top upGrad programs:

Best Machine Learning and AI Courses Online

If you're aiming to build a solid foundation in Machine Learning and AI, there are some excellent free courses available that offer certification. These courses are ideal whether you're exploring AI for the first time or looking to sharpen your skills to meet industry demands. Before diving into the details, here’s a quick overview of the top free ML & AI certification courses and where you can take them.

Platform / Provider	Course Name
upGrad	Introduction to Generative AI – Free Certificate
upGrad	Artificial Intelligence in the Real World – Free Certificate
upGrad	Fundamentals of Deep Learning and Neural Networks – Free Certificate
upGrad	Unsupervised Learning: Clustering – Free Certificate
Microsoft Learn	Microsoft Azure AI Fundamentals – Free Certificate
Google AI	Machine Learning Crash Course with TensorFlow APIs – Free Certificate

Let’s explore what each course offers, who it’s best suited for, and how it can help you build strong AI and machine learning skills, whether you’re a beginner or looking to specialize.

1. Introduction to Generative AI – Free Certificate by upGrad

This beginner-friendly course introduces you to generative AI, covering AI-driven creativity and real-world use cases. Over just 2 hours, you’ll learn about Large Language Models (LLMs), tips & tricks for using generative AI, and how businesses adopt this technology.

AI Skills You’ll Learn:

Basics of generative AI and LLMs
Real-world applications of AI-generated content
Practical insights into enterprise adoption of AI
Hands-on tips for working with AI tools

Who Should Opt for This Course?

Beginners curious about AI creativity
Professionals wanting to apply generative AI in projects
Students exploring AI technologies

2. Artificial Intelligence in the Real World – Free Certificate by upGrad

Explore AI applications across industries like healthcare and finance in this 7-hour course. You’ll learn foundational AI concepts, random variables in AI, and the differences between machine learning and deep learning.

AI Skills You’ll Learn:

Different types of AI and their applications
Machine learning vs. deep learning explained
How AI impacts business operations and decision-making
Strategies for integrating AI into real-world projects

Who Should Opt for This Course?

Anyone interested in practical AI use cases
Students and professionals aiming to understand AI’s business impact
Beginners wanting a broad introduction to AI

3. Fundamentals of Deep Learning and Neural Networks – Free Certificate by upGrad

This 28-hour course gives you a solid foundation in deep learning and neural networks. You’ll study neural network architecture, perceptrons, and training methods, understanding how AI models mimic brain function.

AI Skills You’ll Learn:

Deep learning fundamentals and network structures
Perceptron design and training techniques
How artificial neurons process information
Application of neural networks in AI systems

Who Should Opt for This Course?

Beginners ready to dive deep into AI models
Developers interested in neural network architectures
Students preparing for advanced AI topics

4. Unsupervised Learning: Clustering – Free Certificate by upGrad

Master the core clustering algorithms like K-Means and Hierarchical clustering in this 11-hour course. You’ll apply Python libraries for clustering, explore real-world business cases, and learn how to segment data effectively.

AI Skills You’ll Learn:

Key clustering methods and their differences
Python implementation with Scikit-learn and Seaborn
Practical applications in marketing, fraud detection, and customer profiling
Data preprocessing for unsupervised learning

Who Should Opt for This Course?

Beginners learning unsupervised ML
Data enthusiasts wanting a hands-on Python experience
Marketers and analysts interested in customer segmentation

IIIT Bangalore

Executive Diploma in Machine Learning and AI

Placement Assistance

Executive PG Program12 Months

Liverpool John Moores University

Master of Science in Machine Learning & AI

Dual Credentials

Master's Degree18 Months

If you want to strengthen your foundation in model building and algorithm selection, upGrad’s free Data Structures & Algorithms course is a smart start. Learn sorting, runtime analysis, and practical tools like arrays and stacks, all with expert-led lessons and certification.

Also read: Machine Learning Datasets Project Ideas for Beginners: Real-World Projects to Build Your Portfolio

5. Microsoft Azure AI Fundamentals – Free Certificate by Microsoft Learn

This free course introduces you to AI concepts using Microsoft Azure tools. Over several hours, you’ll get hands-on experience with AI workloads, Azure services, and cognitive APIs, making it ideal if you want to build AI solutions on cloud platforms.

AI Skills You’ll Learn:

Core AI workloads and concepts on Azure
Using Azure Cognitive Services for vision, speech, and language
Building AI models with cloud infrastructure
Basics of responsible AI and ethical considerations

Who Should Opt for This Course?

Beginners interested in AI cloud platforms
IT professionals wanting to learn AI integration on Azure
Developers seeking Azure certification prep

Must Read: Machine Learning Project Ideas for Beginners

6. Machine Learning Crash Course with TensorFlow APIs – Free Certificate by Google AI

This practical crash course uses TensorFlow APIs to teach you key machine learning concepts and techniques. You’ll get hands-on experience with training models, working with datasets, and understanding ML workflow.

AI Skills You’ll Learn:

Fundamentals of machine learning and TensorFlow
Data pipeline creation and feature engineering
Model training, evaluation, and deployment
Real-world ML problem solving with Google tools

Who Should Opt for This Course?

Developers wanting to use TensorFlow for ML projects
Beginners ready for a coding-first approach to ML
Students and professionals looking to solidify ML basics

To get better at choosing and applying the right algorithm for real-world tasks, try upGrad’s free Logistic Regression course. You’ll learn univariate, multivariate models, ROC analysis, and data prep techniques, ideal for finance, marketing, or fraud analytics roles.

Also Read: Machine Learning Applications in Healthcare: What Should We Expect?

Career Opportunities in Machine Learning

Aspiring professionals now have many job options because of the increased need for machine learning expertise. Let’s look at some of the most fascinating jobs in machine learning:

Below is a comparison of some of the most in-demand roles in India, along with their average salary ranges in 2025.

Role	Key Responsibilities	Average Salary (2025)
Machine Learning Engineer	Design, build, and deploy machine learning models and systems. Expert in programming, algorithms, and scaling ML solutions.	₹9.5 – ₹11.5 LPA
Data Scientist	Analyze large datasets, derive insights, and apply statistical and machine learning techniques to solve business problems.	₹10 – ₹37 LPA
AI Researcher	Conduct innovative research to develop new AI/ML models and algorithms. Push the boundaries of AI capabilities.	₹26 – ₹30 LPA
Data Engineer	Build and maintain data infrastructure. Ensure reliable data pipelines for data analysis and machine learning workflows.	₹10 – ₹11 LPA
Business Intelligence Analyst	Use machine learning and analytics to interpret business data and provide insights to stakeholders for strategic decision-making.	₹7.5 – ₹8.2 LPA
Machine Learning Consultant	Help organizations adopt machine learning by identifying use cases, designing solutions, and aligning them with business goals.	₹14 – ₹15.4 LPA

Source: Scaler, Ambitionbox

To start a career in machine learning, you must first master the relevant skills and information. Furthermore, having hands-on experience through projects and internships can considerably increase your chances of landing a machine-learning position.

As the need for machine learning specialists grows, so will the income opportunities. Machine learning professionals fetch lucrative wages because of their specialized expertise and the value they provide to organizations. Furthermore, the profession provides several prospects for advancement and continual learning, making it an intriguing career choice.

Also Read: Top 30 Machine Learning Skills for ML Engineers in 2024

Why Choose upGrad’s Machine Learning Free Online Course?

An excellent first step is to enroll in a free online machine learning course with certification. Enroll in a trusted course that covers the fundamentals, such as algorithms, data processing, model training, and evaluation. The skills you gain will open doors in various fields, such as AI development, data analysis, and automation.

You can choose from plenty of platforms in 2025 to start your journey with a trusted machine learning course. Here's why you should consider one such platform like upGrad:

1 on 1 Industry Mentorship: You get to study exclusively from a leading Machine Learning expert. It would allow you to remove any doubts regarding the subject matter.
Industry-Expert Curriculum: All the courses are the product of seasoned industry experts, who ensure that you understand all the concepts as quickly as possible.
Weekly Live Lectures: Your instructor will give live lectures every week. Live interactions help streamline the learning experience.
Free Certificate: After you complete the machine learning course for free, you’ll get a certificate to enhance your resume.

If you're ready to deepen your AI expertise and start building robust algorithms, here are some additional upGrad courses that can help you upskill and put these techniques into practice.

If you're ready to take the next step in your career, connect with upGrad’s career counseling for personalized guidance. You can also visit a nearby upGrad center for hands-on training to enhance your generative AI skills and open up new career opportunities!

References:
https://www.businessinsider.com/netflix-recommendation-engine-worth-1-billion-per-year-2016-6
https://www.scaler.com/blog/data-scientist-salary-in-india/
https://www.ambitionbox.com/profile/machine-learning-engineer-salary

Frequently Asked Questions (FAQs)

1. What’s the best way to start learning machine learning if I have no prior experience in AI?

2. How do I choose the right machine learning specialization for my career goals?

3. What are the must-have projects to include in my AI portfolio to impress recruiters?

4. How necessary is math knowledge in AI, and which topics should I focus on?

5. Can I learn machine learning effectively without a degree in computer science?

6. How do I stay updated with the latest AI and machine learning advancements?

7. What’s the best way to transition from traditional software development to AI and machine learning roles?

8. How do I handle imbalanced datasets in machine learning projects?

9. Which programming languages and tools should I focus on to build a career in AI?

10. How important is deep learning compared to classical machine learning techniques?

11. What career paths are available for machine learning engineers versus data scientists?

Pavan Vadapalli

900 articles published

Director of Engineering @ upGrad. Motivated to leverage technology to solve problems. Seasoned leader for startups and fast moving orgs. Working on solving problems of scale and long term technology s...

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