Machine Learning Courses & Certifications Online

Machine learning (ML) is a branch of artificial intelligence (AI) that enables systems to learn and improve from experience without being explicitly programmed. It focuses on the development of algorithms that can analyze and interpret data to make predictions or decisions.

Key Concepts of Machine Learning

Types of Machine Learning

Supervised Learning: Involves training a model on labeled data, meaning the input data comes with corresponding output labels. Examples include classification and regression tasks.
Unsupervised Learning: Deals with unlabeled data. The model tries to find patterns or intrinsic structures in the input data. Examples include clustering and association.
Reinforcement Learning: Involves training a model to make sequences of decisions by rewarding or penalizing it based on its actions. It's commonly used in game playing and robotics.

Related: Different

Key Concepts of Machine Learning

Types of Machine Learning

Supervised Learning: Involves training a model on labeled data, meaning the input data comes with corresponding output labels. Examples include classification and regression tasks.
Unsupervised Learning: Deals with unlabeled data. The model tries to find patterns or intrinsic structures in the input data. Examples include clustering and association.
Reinforcement Learning: Involves training a model to make sequences of decisions by rewarding or penalizing it based on its actions. It's commonly used in game playing and robotics.

Key Algorithms of Machine Learning

Linear Regression: Used for predicting a continuous value.
Logistic Regression: Used for binary classification problems.
Decision Trees: Used for both classification and regression tasks.
Support Vector Machines (SVM): Used for classification tasks.
Neural Networks: Form the basis of deep learning, useful for complex pattern recognition tasks.

Why Learn Machine Learning in 2024?

Learning machine learning in 2024 is an excellent decision for several reasons. The field continues to grow rapidly, offering numerous career opportunities and applications across various industries. Here are some key reasons to learn machine learning in 2024:

High demand and growth: The demand for AI and machine learning specialists is projected to increase by 40% from 2023 to 2027. As data generation and the need for data-driven decision-making grow across industries, the job market for machine learning professionals is expanding rapidly.
Lucrative salaries: Machine learning jobs are among the highest-paying in the tech industry. Roles like Data Scientist, AI Engineer, and Machine Learning Engineer command salaries ranging from INR 15-25 Lacs. The scarcity of machine learning talent makes it an attractive and rewarding career path.
Intellectual challenge: Machine learning presents a dynamic landscape of complex problems to solve. The field requires constant learning and adaptation to new technologies and methodologies, making it an exciting area for problem-solvers and those passionate about pushing the boundaries of what machines can do.
Broad applications: Machine learning has applications in virtually every industry, from healthcare and education to finance and marketing. Learning ML skills can open up opportunities across diverse sectors and enable you to make a significant impact.
Automation and efficiency: ML enables businesses to automate tasks, improve operations, and gain valuable insights from data. Professionals with ML expertise are valuable assets in helping organizations leverage data to drive innovation and growth.

What Topics Are Typically Covered in Machine Learning Courses?

Category	Topics	Details
Introduction to Machine Learning	Definition and Scope History and Evolution Types of Machine Learning	Understanding ML, its applications, and its evolution Supervised, Unsupervised, and Reinforcement Learning
Mathematics and Statistics for Machine Learning	Linear Algebra Calculus Probability and Statistics Optimization Techniques	Vectors, matrices, eigenvalues, eigenvectors Differentiation, integration, partial derivatives Probability distributions, hypothesis testing Gradient descent, convex optimization
Data Preprocessing and Exploration	Data Cleaning Data Transformation Exploratory Data Analysis (EDA)	Handling missing values, outlier detection Normalization, standardization, encoding categorical variables Visualization techniques, feature engineering
Supervised Learning Algorithms	Regression Algorithms Classification Algorithms Ensemble Methods	Linear regression, logistic regression Decision trees, SVM, KNN, naive Bayes Random forests, GBM, XGBoost
Unsupervised Learning Algorithms	Clustering Dimensionality Reduction	K-means, hierarchical clustering, DBSCAN PCA, t-SNE
Advanced Topics in Machine Learning	Neural Networks and Deep Learning Natural Language Processing (NLP) Reinforcement Learning	Basics of neural networks, CNNs, RNNs, GANs Text processing, sentiment analysis, topic modeling Q-learning, DQNs, policy gradients
Model Evaluation and Validation	Metrics for Evaluation Validation Techniques Hyperparameter Tuning	Accuracy, precision, recall, F1 score, ROC-AUC Cross-validation, train-test split, overfitting, underfitting Grid search, random search, Bayesian optimization
Practical Implementation	Programming Languages and Tools Machine Learning Libraries Deployment of Models	Python, R, Jupyter notebooks Scikit-learn, TensorFlow, Keras, PyTorch Model saving and loading, creating APIs, using cloud platforms
Special Topics and Case Studies	Ethics in AI Case Studies Capstone Projects	Bias in ML, fairness, transparency Real-world applications in healthcare, finance, e-commerce End-to-end projects covering all ML stages

Must Read - Top 10 Machine Learning Projects for Beginners

How To Choose The Best Machine Learning Courses For Your Career Goal?

Here’s a step-by-step guide to help you make an informed decision:

1. Assess Your Current Skill Level

Beginner: If you are new to machine learning, look for courses that cover the basics and provide a solid foundation. Courses should start with fundamental concepts and gradually introduce more complex topics.
Intermediate: If you have some experience with machine learning, choose courses that delve into advanced algorithms and applications.
Advanced: For those with substantial knowledge, look for specialized courses or advanced topics like deep learning, reinforcement learning, or specific industry applications.

2. Define Your Career Goals

Data Scientist: Look for courses that cover a broad range of machine learning algorithms, data preprocessing, and model evaluation techniques.
AI Engineer: Focus on courses that include programming and implementation of machine learning models, particularly using frameworks like TensorFlow or PyTorch.
Researcher: Opt for courses that emphasize theoretical concepts, mathematics, and cutting-edge research in machine learning.

3. Check Course Content and Structure

Core Topics: Ensure the course covers essential machine learning topics like supervised and unsupervised learning, neural networks, and model evaluation.
Hands-On Projects: Practical experience is crucial. Look for courses that include projects or labs where you can apply what you’ve learned.
Programming Languages: Most machine learning courses use Python. Ensure you are comfortable with the programming language used in the course.

4. Evaluate the Instructor’s Credentials

Expertise: Check the instructor’s background in machine learning and their professional experience.
Teaching Style: Look for reviews or sample lectures to see if their teaching style matches your learning preference.

5. Consider Course Format and Flexibility

Self-Paced vs. Scheduled: Decide if you prefer self-paced courses that allow you to learn at your own speed or scheduled courses with fixed deadlines.
Interactive Elements: Courses with interactive elements like forums, Q&A sessions, and peer reviews can enhance your learning experience.

6. Read Reviews and Testimonials

Student Feedback: Reviews from past students can provide insights into the course quality, content relevance, and instructor effectiveness.
Course Ratings: Platforms like Coursera, edX, and Udemy often have ratings for their courses. Look for highly-rated courses with positive feedback.

7. Compare Costs and Certification

Budget: Consider the cost of the course and whether it fits your budget. Some platforms offer financial aid or scholarships.
Certification: If a certificate is important for your career goals, ensure the course offers a recognized certification upon completion.

Must Read: Difference Between AI & ML

Best Machine Learning Courses For You

Course Name	Platform	Institution	Instructor	Duration	Level
Machine Learning	Coursera	Stanford University	Andrew Ng	11 weeks	Intermediate
Machine Learning A-Z™: Hands-On Python & R In Data Science	Udemy	-	Kirill Eremenko, Hadelin de Ponteves	41.5 hours	All Levels
Deep Learning Specialization	Coursera	DeepLearning.AI	Andrew Ng	5 months	Advanced
Python for Data Science and Machine Learning Bootcamp	Udemy	-	Jose Portilla	25 hours	Beginner
Machine Learning for Data Science and Analytics	edX	Columbia University	-	12 weeks	Introductory
Applied AI with DeepLearning	Coursera	IBM	-	5 months	Intermediate
Machine Learning Specialization	Coursera	University of Washington	-	8 months	Advanced
Introduction to TensorFlow for AI, Machine Learning, and Deep Learning	Coursera	DeepLearning.AI	Andrew Ng	4 weeks	Beginner
Machine Learning with Python	edX	IBM	-	5 weeks	Introductory
Advanced Machine Learning Specialization	Coursera	National Research University Higher School of Economics	-	7 months	Advanced

Must Explore - Top 10 Free Machine Learning Courses to Take Up in 2023

Machine Learning Courses on Coursera

Course Name	Institution	Duration	Level
Machine Learning	Stanford University	11 weeks	Intermediate
Deep Learning Specialization	DeepLearning.AI	5 months	Advanced
AI For Everyone	DeepLearning.AI	4 weeks	Beginner
Machine Learning for Everyone	University of London	4 weeks	Beginner
Applied AI with DeepLearning	IBM	5 months	Intermediate
Machine Learning Specialization	University of Washington	8 months	Advanced
Introduction to TensorFlow for Artificial Intelligence, Machine Learning...	DeepLearning.AI	4 weeks	Beginner
Python and Machine Learning for Data Science	IBM	4 months	Beginner
Advanced Machine Learning Specialization	National Research University Higher School of Economics	7 months	Advanced
Structuring Machine Learning Projects	DeepLearning.AI	2 weeks	Intermediate

Explore - Coursera Machine Learning Courses

Machine Learning Courses on Udemy

Course Name	Instructor	Duration	Level
Machine Learning A-Z™: Hands-On Python & R In Data Science	Kirill Eremenko, Hadelin de Ponteves	41.5 hours	All Levels
Python for Data Science and Machine Learning Bootcamp	Jose Portilla	25 hours	Beginner
Machine Learning, Data Science and Deep Learning with Python	Frank Kane	15.5 hours	Beginner
Deep Learning A-Z™: Hands-On Artificial Neural Networks	Kirill Eremenko, Hadelin de Ponteves	23.5 hours	All Levels
Complete Machine Learning & Data Science Bootcamp 2023	365 Careers	36.5 hours	All Levels
Machine Learning with Python	Jose Portilla	21.5 hours	Beginner
Advanced AI: Deep Reinforcement Learning in Python	Lazy Programmer Inc.	17 hours	Advanced
The Data Science Course 2023: Complete Data Science Bootcamp	365 Careers	28 hours	Beginner
Mathematics for Machine Learning	SuperDataScience Team	10.5 hours	Beginner
Bayesian Machine Learning in Python: A/B Testing	Lazy Programmer Inc.	11.5 hours	Intermediate

Explore: Udemy Machine Learning Course

Machine Learning Courses on edX

Course Name	Institution	Duration	Level
Machine Learning with Python: from Linear Models to Deep Learning	IBM	5 weeks	Introductory
Principles of Machine Learning	Microsoft	6 weeks	Intermediate
Machine Learning for Data Science and Analytics	Columbia University	12 weeks	Introductory
MicroMasters Program in Artificial Intelligence	Columbia University	10 months	Advanced
Machine Learning	University of Washington	10 weeks	Intermediate
Artificial Intelligence: Principles and Techniques	Columbia University	12 weeks	Intermediate
Machine Learning for Everyone	Microsoft	6 weeks	Introductory
Deep Learning	IBM	6 weeks	Intermediate
Advanced Machine Learning	Harvard University	8 weeks	Advanced
Machine Learning and Reinforcement Learning in Finance	New York University	8 weeks	Intermediate

Explore - edX Machine Learning Courses

Top Free Machine Learning Courses

Course Name	Platform	Institution	Instructor	Duration	Level
Machine Learning	Coursera	Stanford University	Andrew Ng	11 weeks	Intermediate
Deep Learning Specialization	Coursera	DeepLearning.AI	Andrew Ng	5 months	Advanced
AI For Everyone	Coursera	DeepLearning.AI	Andrew Ng	4 weeks	Beginner
Machine Learning for Everyone	Coursera	University of London	-	4 weeks	Beginner
Applied AI with DeepLearning	Coursera	IBM	-	5 months	Intermediate
Machine Learning Specialization	Coursera	University of Washington	-	8 months	Advanced
Introduction to TensorFlow for AI, Machine Learning, and Deep Learning	Coursera	DeepLearning.AI	Andrew Ng	4 weeks	Beginner
Machine Learning with Python	edX	IBM	-	5 weeks	Introductory
Advanced Machine Learning Specialization	Coursera	National Research University Higher School of Economics	-	7 months	Advanced
Python and Machine Learning for Data Science	Coursera	IBM	-	4 months	Beginner

Must Check - Top 10 Free Machine Learning Courses

What Career Opportunities You Can Pursue with a Certification in Machine Learning?

There are a lot of machine learning jobs available that you can do once you complete your certification or degree in machine learning.

Let’s have a glimpse of some of the job opportunities.

Job Title	Job Description	Skills Required	Potential Employers	Average Salary (INR)
Machine Learning Engineer	Develop and implement ML models, algorithms, and solutions.	Python, R, TensorFlow, PyTorch, data preprocessing, model deployment	TCS, Infosys, Wipro, Accenture, HCL Technologies	8-20 LPA
Data Scientist	Analyze and interpret complex data, build predictive models, and provide data-driven insights.	Statistics, Python, R, SQL, data visualization, machine learning	IBM, Mu Sigma, Fractal Analytics, ZS Associates, Cognizant	6-18 LPA
AI/ML Research Scientist	Conduct research to advance the field of AI/ML and develop new algorithms and models.	Deep learning, neural networks, research methodologies, programming	Google Research, Microsoft Research, IBM Research, academic institutions	10-25 LPA
Data Analyst	Collect, process, and perform statistical analysis on data sets to provide business insights.	SQL, Excel, Python, R, data visualization, statistical analysis	Deloitte, KPMG, EY, PwC, Capgemini	4-10 LPA
Business Intelligence (BI) Developer	Design and develop BI solutions, including data warehouses, dashboards, and reports.	SQL, data modeling, BI tools (Tableau, Power BI), Python	TCS, Cognizant, Infosys, Wipro, Tech Mahindra	5-12 LPA
Big Data Engineer	Design, develop, and manage big data infrastructure and tools.	Hadoop, Spark, Kafka, NoSQL databases, Python, Java	Amazon, Flipkart, Paytm, Reliance Jio, Ola	7-15 LPA
Natural Language Processing (NLP) Engineer	Develop systems that can understand and interpret human language.	NLP techniques, Python, TensorFlow, PyTorch, linguistics	Google, Amazon, Microsoft, TCS, Infosys	8-18 LPA
Computer Vision Engineer	Develop algorithms and models to process and analyze visual data from images and videos.	OpenCV, TensorFlow, PyTorch, Python, deep learning	NVIDIA, Intel, Qualcomm, Samsung, startups in AI	9-20 LPA
Robotics Engineer	Design and develop robotic systems that can perform specific tasks using AI/ML.	Robotics, Python, ROS, machine learning, control systems	ISRO, DRDO, iRobot, GreyOrange, startups in robotics	6-15 LPA
AI Product Manager	Oversee the development and deployment of AI/ML products, bridging the gap between technical and business teams.	Product management, machine learning, business strategy, communication skills	Google, Microsoft, Amazon, startups in AI	12-30 LPA

Top Colleges Offering Bachelor’s Degrees in Machine Learning

Program Name	University	Duration	Degree Type
B.Tech in Computer Science and Engineering with specialization in Artificial Intelligence and Machine Learning	Vellore Institute of Technology (VIT)	4 years	Bachelor's
B.Tech in Computer Science and Engineering with specialization in Artificial Intelligence and Machine Learning	SRM Institute of Science and Technology	4 years	Bachelor's
B.Tech in Computer Science and Engineering with specialization in Data Science and Machine Learning	Amity University	4 years	Bachelor's
B.Tech in Computer Science and Engineering with specialization in Artificial Intelligence and Machine Learning	Manipal Academy of Higher Education (MAHE)	4 years	Bachelor's
B.Tech in Artificial Intelligence and Data Science	Lovely Professional University (LPU)	4 years	Bachelor's
B.Tech in Artificial Intelligence and Machine Learning	Chitkara University	4 years	Bachelor's
B.Tech in Computer Science and Engineering with specialization in Artificial Intelligence and Machine Learning	Jain University	4 years	Bachelor's
B.Tech in Computer Science and Engineering with specialization in Artificial Intelligence and Machine Learning	Chandigarh University	4 years	Bachelor's
B.Tech in Computer Science and Engineering with specialization in Artificial Intelligence and Machine Learning	Reva University	4 years	Bachelor's
B.Tech in Computer Science and Engineering with specialization in Artificial Intelligence and Machine Learning	Kalinga Institute of Industrial Technology (KIIT)	4 years	Bachelor's

Top Colleges Offering Master’s Degrees in Machine Learning

Program Name	University	Duration	Degree Type
M.Tech in Machine Learning and Artificial Intelligence	Indian Institute of Technology (IIT) Bombay	2 years	Master's
M.Tech in Artificial Intelligence and Machine Learning	Indian Institute of Technology (IIT) Delhi	2 years	Master's
M.Tech in Data Science and Machine Learning	Indian Institute of Technology (IIT) Madras	2 years	Master's
M.Tech in Artificial Intelligence	Indian Institute of Technology (IIT) Hyderabad	2 years	Master's
M.Tech in Machine Learning and Data Analytics	Indian Institute of Technology (IIT) Kharagpur	2 years	Master's
M.Tech in Data Science and Machine Learning	Indian Institute of Science (IISc) Bangalore	2 years	Master's
M.Tech in Artificial Intelligence and Machine Learning	National Institute of Technology (NIT) Trichy	2 years	Master's
M.Tech in Artificial Intelligence and Machine Learning	International Institute of Information Technology (IIIT) Hyderabad	2 years	Master's
M.Tech in Data Science and Machine Learning	Birla Institute of Technology and Science (BITS) Pilani	2 years	Master's
M.Tech in Machine Learning	Amrita Vishwa Vidyapeetham, Coimbatore	2 years	Master's

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Core ML: Machine Learning for iOS

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Intro to TensorFlow for Deep Learning

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Create Image Captioning Models with Google Cloud

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