9 Best AI & Machine Learning Courses (Free + Paid) with Certificate
Are you ready to boost your career with the power of AI and Machine Learning?
By 2030, AI is projected to create 97 million new jobs and drive the global market to a staggering $826 billion.
The demand for skilled professionals is skyrocketing, with salaries for AI specialists averaging $153,929 per year.
In this guide, I hand-picked the best free and paid Machine Learning and AI courses that come with certificates, ensuring you get the most value and recognition.
But before I give you the list, I want to tell you that Machine Learning and AI are deep and extensive subjects. If you are genuinely interested in learning them, I suggest considering a paid course. Trust me, investing in a good course can be a game-changer for your career.
Before you start learning machine learning and AI, it is important to choose a programming language.
I suggest you choose Python because it is easy to learn and highly in demand in the job market. I have provided a list of top free Python courses with certificates for your convenience. You can check them out below.
Are you ready to enter the machine learning and AI journey?
5 Best Free Machine Learning Courses
Artificial Intelligence and Machine Learning by ISRO (Bonus Course)
The “Artificial Intelligence and Machine Learning for Geospatial Data Analysis” course by the Indian Institute of Remote Sensing (IIRS) introduces essential AI and ML concepts tailored for geospatial data analysis. It covers fundamentals like supervised and unsupervised learning, deep learning, and neural networks, with practical applications in geospatial contexts. The course also explores advanced topics such as image classification and object detection, making it ideal for students, researchers, and professionals looking to enhance their skills in AI and ML for geospatial analysis.
Course Overview
| Course Title | Artificial Intelligence and Machine Learning for Geospatial Data Analysis |
|---|---|
| Institution | Indian Institute of Remote Sensing (IIRS) |
| Duration | 2 Weeks (August 19-24, 2024) |
| Mode | Online |
| Prerequisites | Basic knowledge of geospatial data and remote sensing |
| Key Topics | AI and ML fundamentals, supervised and unsupervised learning, deep learning, image classification, object detection, geospatial applications |
| Instructor(s) | Experts from IIRS |
| Assessment | Final assessment at the end of the course |
| Certification | Participants will receive a certificate upon successful completion |
What Learners Will Gain
- Understanding AI and ML: Gain a strong foundation in AI and ML concepts, specifically tailored for geospatial data.
- Practical Skills: Learn to apply AI and ML techniques to real-world geospatial problems, including image classification and object detection.
- Advanced Techniques: Explore deep learning and neural networks within the context of geospatial data analysis.
- Enhanced Decision-Making: Develop skills in data-driven decision-making using AI and ML tools.
Who Should Enroll
- Geospatial Analysts: Professionals involved in geospatial data analysis looking to integrate AI and ML into their workflows.
- Researchers: Those interested in the latest advancements in AI and ML applications in remote sensing and geospatial data.
- Students: Individuals studying geospatial sciences, remote sensing, or related fields who want to expand their knowledge in AI and ML.
1. Deep Dive into Deep Learning by Scaler
This free course is designed for beginners and provides a comprehensive introduction to deep learning. The course is taught by Srikanth Varma, a seasoned expert in data science and machine learning, with over 13 years of experience in the field. The course aims to equip learners with essential deep learning skills, including understanding neural networks, proficiency in popular deep learning frameworks like TensorFlow and PyTorch, and problem-solving capabilities through real-world projects. Additionally, students will learn to interpret and communicate the results of deep learning models effectively.
Course Details
| Feature | Details |
|---|---|
| Instructor | Srikanth Varma |
| Duration | 13 hours 6 minutes (3 Modules) |
| Language | English (Audio and Subtitles) |
| Course Level | Advanced |
| Certificate | Included (Certificate of Excellence) |
| Enrollment | 5228 students enrolled |
| Challenges | 3 Challenges |
| Modules and Lessons | 3 Modules, 51 Lessons |
| Learning Format | Self-paced learning with unlimited access |
| Pre-requisites | Basic programming knowledge (preferably Python), understanding of machine learning, and basic mathematics (linear algebra, calculus, statistics) |
| Skills Acquired | Deep learning concepts, proficiency in TensorFlow and PyTorch, problem-solving, interpretation, and communication of results |
| Target Audience | Aspiring AI and ML professionals, software engineers, data scientists, analysts, researchers, and academics |
| Additional Features | Expert-led learningStructured curriculum1:1 mentorship sessionsCareer support |
Instructor Profile
- Lead DSML Instructor at Scaler
- Over 2000 students on Scaler Platform
- 600+ hours of lectures delivered
- 5-star instructor rating
- Co-Founder & Principal Instructor at Applied AI & AppliedRoots
- Senior ML Scientist at Amazon
- Masters from IISc Bangalore, Gate 2007 (AIR 2)
- Co-Founder of Matherix Labs
- Research Engineer at Yahoo! Labs
Who Should Enroll?
- Aspiring AI and ML professionals
- Software engineers looking to expand their skills
- Data scientists and analysts
- Researchers and academics in fields related to AI and machine learning
2. Free Online Machine Learning Certification Course by Intellipaat
This course is designed to provide a strong foundation in machine learning, helping you build the skills needed to advance in your career. Created by top machine learning experts, this self-paced course covers essential concepts such as data preprocessing, time series, text mining, supervised and unsupervised learning, and more. This course is suitable for anyone looking to start a career in machine learning. With 5 hours of self-paced learning, quizzes, and assignments, you will gain a solid understanding of machine learning fundamentals. Upon completion, you will receive a free certification that can enhance your professional profile.
Course Details
| Feature | Details |
|---|---|
| Instructor | Top ML Experts |
| Duration | 5 Hours (Self-Paced Learning) |
| Language | English |
| Certificate | Included (Certification and Lifetime Access) |
| Enrollment | Open for everyone |
| Learning Format | Self-paced learning with unlimited access |
| Pre-requisites | No prior knowledge required, but interest in Mathematics and Statistics is beneficial |
| Skills Acquired | Machine learning concepts, supervised and unsupervised learning, regression analysis, Python programming |
| Target Audience | Aspiring machine learning engineers, data scientists, AI professionals, and anyone interested in ML |
| Course Content | Module 1: Machine Learning using Python Module 2: Supervised Learning Algorithm in Python |
| Additional Features | Quizzes, Assignments, Career Transition Support, Reviews and Testimonials |
Course Modules
Module 1: Machine Learning using Python
- Introduction to Machine Learning
- Types of Machine Learning
- Applications of Machine Learning
- Machine Learning Demo
Module 2: Supervised Learning Algorithm in Python
- Introduction to Regression
- Step-by-Step Calculation of Linear Regression
- Linear Regression in Python
- Linear Regression Demo
- Step-by-Step Calculation of Logistic Regression
Skills You Will Learn
- Machine Learning: Understanding the basics and applications of machine learning.
- Modeling: Building and evaluating machine learning models.
- Supervised Learning: Learning techniques for regression and classification.
- Unsupervised Learning: Understanding clustering and association techniques.
- Python Programming: Implementing machine learning algorithms using Python.
- Regression Analysis: Performing linear and logistic regression.
Career Opportunities
Completing this course can open up various career opportunities, including roles such as:
- Machine Learning Engineer
- Data Scientist
- AI Specialist
- Business Analyst
- Information Architect
https://intellipaat.com/academy/course/machine-learning-free-course
3. Machine Learning Certification Course for Beginners by Analytics Vidhya
This free course is designed to provide a solid foundation in machine learning and equip you with the skills to build and improve machine learning models. You will learn the basics of machine learning, Python programming, feature engineering techniques, and how to evaluate machine learning models effectively. The course is ideal for aspiring data scientists and anyone interested in understanding machine learning from scratch. No prior data science or machine learning knowledge is required, making it accessible to beginners.
Course Details
| Feature | Details |
|---|---|
| Instructor | Analytics Vidhya Experts |
| Duration | 6 – 8 weeks (8 – 10 hours per week) |
| Language | English |
| Certificate | Included (Blockchain-enabled Certificate with lifetime validity) |
| Enrollment | Open for everyone |
| Learning Format | Self-paced learning with unlimited access |
| Pre-requisites | No prior knowledge required, but interest in Mathematics and Statistics is beneficial |
| Skills Acquired | Machine learning basics, Python programming, supervised and unsupervised learning, regression analysis, feature engineering |
| Target Audience | Aspiring data scientists, AI professionals, and anyone interested in machine learning |
| Course Content | Module 1: Python for Data Science Module 2: Statistics and Exploratory Data Analysis Module 3: Basics of Machine Learning Module 4: Evaluation Metrics Module 5: Feature Engineering |
| Projects | Project 1: Customer Churn Prediction Project 2: NYC Taxi Trip Duration Prediction |
https://courses.analyticsvidhya.com/courses/Machine-Learning-Certification-Course-for-Beginners
4. Deep Learning for Beginners by Simplilearn
Free Deep Learning Course with Certificate offered by Simplilearn. This beginner-level course provides a comprehensive introduction to deep learning, a crucial area of artificial intelligence. Designed for beginners, the course covers the fundamentals of deep learning, including neural networks, TensorFlow, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and deep learning applications. This self-paced course includes 7 hours of video lessons, offering flexibility to learn at your own pace. Upon completion, you will receive a certificate that can be shared with potential employers and added to your professional network.
Course Details
| Feature | Details |
|---|---|
| Instructor | Simplilearn Experts |
| Duration | 7 Hours |
| Language | English |
| Certificate | Included (Completion Certificate) |
| Access | 90 Days of Access to the Course |
| Learning Format | Self-paced video lessons |
| Pre-requisites | Basic awareness of Python programming, mathematics, and statistics |
| Skills Acquired | Neural Networks, TensorFlow, Deep Learning Libraries, CNNs, RNNs, Deep Learning Frameworks |
| Target Audience | Software Engineers, Data Scientists, Data Analysts, Statisticians |
| Course Content | Lesson 1: Introduction to Deep Learning and Its Applications Lesson 2: Neural Networks Lesson 3: Challenges in Training Neural Networks Lesson 4: Top Deep Learning Libraries Lesson 5: TensorFlow and Data Flow Graphs Lesson 6: Use Case Implementation using TensorFlow Lesson 7: TensorFlow Object Detection Lesson 8: Deep Learning Frameworks Lesson 9: Image Recognition Lesson 10: Types of Recurrent Neural Networks Lesson 11: LSTMs Lesson 12: Deep Learning Applications Lesson 13: Interview Questions Lesson 14: Knowledge Check |
| Career Opportunities | Machine Learning Engineer, Data Scientist, AI Specialist |
https://www.simplilearn.com/introduction-to-deep-learning-free-course-skillup
5. Free AI & Machine Learning Courses by UpGrad with Certificate
UpGrad provides many free Machine Learning courses; the good part is they are detailed courses about Machine Learning and come with a free certificate. I would definitely recommend you to check out these courses:
| Course Title | Description | Duration |
|---|---|---|
| Artificial Intelligence in the Real World | This free course will help you learn about the applications of AI in both service and non-service industries. You’ll also be able to leverage this knowledge to understand and appreciate the role of AI in different sectors. | 7 hours |
| Case Study using Tableau, Python and SQL | This course will help you apply your knowledge in SQL, Python, and Tableau through a practical case study. You will learn to combine these technologies to develop a business solution for a churn problem. | 10 hours |
| Introduction to Tableau | In this free course, you’ll learn about data analytics and ways to transform data into actionable insights using Tableau. Additionally, you’ll discover how to visualize data and about various chart types in Tableau. | 8 hours |
| Data Science in E-commerce | This course will help you acquire skills used in the E-commerce sector to make key business decisions using data. Topics covered include Recommendation Systems, Price Optimization, Market Mix Modeling, and A/B Testing. | 13 hours |
| Introduction to Natural Language Processing | This AI course will help you take your first steps towards understanding the interaction between human language and computers. It covers the basics of NLP and topics such as RegEx for building tools for spell correction, phonetic hashing, and spam detection. | 11 hours |
| Fundamentals of Deep Learning of Neural Networks | This beginner-friendly course introduces you to the most sophisticated and cutting-edge models in machine learning, such as Artificial Neural Networks (ANNs). You will learn the basics of Neural Networks and various concepts related to Deep Learning. | 28 hours |
| Linear Algebra for Analysis | This introductory course covers Linear Algebra required for analytics. Topics such as vectors, linear transformations, matrices, eigenvalues, and eigenvectors will be explained. | 5 hours |
| Hypothesis Testing Crash Course | This course introduces you to Hypothesis Testing and covers everything from scratch. You will learn about the types of hypotheses, decision-making criteria, critical value, and p-value methods for testing hypotheses. | 11 hours |
| Basics of Inferential Statistics | This course will help you learn how to use random sample data to describe and make inferences about a population. You’ll learn about probability, statistics, continuous and discrete probability distributions, sampling methods, and error quantification. | 15 hours |
| Unsupervised Learning: Clustering | This course is designed to help you master Clustering in Unsupervised Learning, covering basic introduction to Clustering, K-Means Clustering and its execution, and Hierarchical Clustering. | 11 hours |
| Logistic Regression for Beginners | This course covers the concept of Logistic Regression and its applications in industry, including univariate and multivariate logistic regression in detail. | 17 hours |
| Linear Regression – Step by Step Guide | This course introduces you to the concept of regression, covering simple and multiple linear regression, and their relevance in various industries. | 21 hours |
| Learn Python Libraries: NumPy, Matplotlib and Pandas | This preparatory course will build your knowledge of Python programming, focusing on important libraries for handling data: NumPy, Matplotlib, and Pandas. | 15 hours |
https://www.upgrad.com/free-courses
Top 4 Premium Machine Learning & AI Courses with Certificate
Now, you might ask, why choose a premium course? Machine learning is highly technical and requires deep understanding. A paid course is a smart investment if you’re serious about mastering it. It offers structured learning, expert guidance, hands-on projects, and valuable certification, all enhancing your skills and career prospects.
1. Artificial Intelligence Engineer by Simplilearn
The Master’s in Artificial Intelligence program by Simplilearn, in collaboration with IBM, is an excellent choice for anyone looking to advance their career in AI. With a structured curriculum, expert-led sessions, real-world projects, and industry-recognized certifications, this program provides a comprehensive learning experience that equips you with the skills and credentials needed to succeed in the field of artificial intelligence.
Course Details
| Feature | Details |
|---|---|
| Instructor | Simplilearn and IBM Experts |
| Duration | 11 Months |
| Learning Format | Online Bootcamp |
| Certificate | Industry-recognized AI Engineer certificate from Simplilearn and IBM certificates |
| Access | Lifetime access to self-paced learning content |
| Next Cohort Start Date | 29th June, 2024 |
| Skills Covered | Generative AI, Prompt Engineering, Python Programming, Deep Learning, NLP, TensorFlow, and more |
| Tools Covered | Python, TensorFlow, Keras, Scikit-Learn, NLTK, OpenCV, and more |
| Projects | Sales Analysis, Growth Planning, Employee Turnover Analytics, Segmentation of Songs, House Loan Data Analysis |
Key Features
| Feature | Details |
|---|---|
| Industry-recognized Certificate | Earn an AI Engineer certificate from Simplilearn and IBM certifications |
| Live Sessions | Attend live sessions by industry experts and IBM masterclasses |
| Hands-on Projects | Work on real-world projects and capstone projects from 3 domains |
| Hackathons and AMAs | Participate in exclusive hackathons and Ask-Me-Anything sessions with IBM leadership |
| Career Support | Access to dedicated career support services |
| 24/7 Support | 24/7 learning assistance and support |
Course Curriculum
Learning Path
- Essentials of Generative AI, Prompt Engineering & ChatGPT
- Programming Essentials
- Python for Data Science by IBM
- Applied Data Science with Python
- Machine Learning using Python
- Deep Learning Specialization
- AI Engineer Capstone
Electives:
- Deep Learning with Keras and TensorFlow by IBM
- ADL & Computer Vision
- Natural Language Processing (NLP)
- Reinforcement Learning
- Advanced Generative AI
Career Opportunities
| Role | Average Salary | Companies Hiring |
|---|---|---|
| Machine Learning Engineer | $76K – $154K per annum | Various industries |
| AI Specialist | $100K+ per annum | Leading tech firms |
| Data Scientist | High demand across sectors |
Why Choose This Program?
Becoming an AI engineer opens up numerous opportunities across various industries, from healthcare to finance and retail. AI engineers are in high demand, with a significant growth rate projected for the coming years. This program not only provides you with the knowledge and skills needed but also offers valuable certifications and hands-on experience, making you job-ready and competitive in the market.
https://www.simplilearn.com/masters-in-artificial-intelligence
2. Post Graduate Programme in Machine Learning & AI (Executive) by upGrad
Machine Learning and AI Post Graduate Diploma Program offered by UpGrad in collaboration with IIIT Bangalore. This comprehensive program is designed to equip you with the essential skills and knowledge needed to excel in the fields of machine learning and artificial intelligence. The curriculum covers various topics, including Python programming, machine learning algorithms, deep learning, natural language processing (NLP), and more. The program is ideal for professionals and graduates who aim to transition into the field of AI and ML or enhance their existing skills. With expert-led live sessions, hands-on projects, and personalized mentorship, this program ensures you gain practical experience and industry-relevant expertise.
Course Details
| Feature | Details |
|---|---|
| Instructor | IIIT Bangalore Faculty and Industry Experts |
| Duration | 12 Months |
| Learning Format | Online |
| Certificate | Post Graduate Diploma from IIIT Bangalore |
| Skills Covered | Python Programming, Machine Learning, Deep Learning, NLP, Computer Vision, Reinforcement Learning, and more |
| Tools Covered | Python, TensorFlow, Keras, Scikit-learn, NLTK, OpenCV, and more |
| Projects | Predictive Analysis, Image Recognition, Sentiment Analysis, and more |
| Prerequisites | Basic knowledge of programming and mathematics |
| Cost | ₹2,85,000 (inclusive of taxes) |
Key Features
| Feature | Details |
|---|---|
| Certification | Earn a Post Graduate Diploma from IIIT Bangalore upon successful completion |
| Expert Instructors | Learn from top faculty at IIIT Bangalore and industry experts |
| Hands-on Learning | Engage in real-world projects and case studies to apply your knowledge |
| Personalized Mentorship | Receive one-on-one mentorship and career guidance from industry professionals |
| Flexible Learning | Study at your own pace with a mix of live sessions, recorded lectures, and self-paced learning materials |
| Career Assistance | Access to job placement support, resume building, and interview preparation |
| Networking Opportunities | Connect with peers and professionals through the UpGrad alumni network |
Course Curriculum
Module 1: Preparatory Course
- Introduction to Python Programming
- Basics of Machine Learning
Module 2: Machine Learning Techniques
- Supervised and Unsupervised Learning
- Regression and Classification
- Ensemble Learning
Module 3: Deep Learning
- Neural Networks
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
Module 4: Natural Language Processing
- Text Processing
- Sentiment Analysis
- Language Modeling
Module 5: Advanced Topics
- Reinforcement Learning
- Computer Vision
- Generative Adversarial Networks (GANs)
Module 6: Capstone Project
- Apply your learning to a comprehensive project that simulates real-world problems
Career Opportunities
| Role | Average Salary | Hiring Companies |
|---|---|---|
| Machine Learning Engineer | ₹8 – 16 LPA | Tech Mahindra, Accenture, TCS, and more |
| Data Scientist | ₹10 – 20 LPA | Infosys, IBM, Cognizant, and more |
| AI Specialist | ₹12 – 24 LPA | Google, Microsoft, Amazon, and more |
Why Choose This Program?
This Post Graduate Diploma in Machine Learning and AI by UpGrad and IIIT Bangalore offers a rigorous curriculum, expert mentorship, and hands-on projects that prepare you for a successful career in AI and ML. The program provides valuable certification and practical skills that are highly sought after in the job market, making it a worthwhile investment for your professional growth.
https://www.upgrad.com/machine-learning-ai-pgd-iiitb
3. Machine Learning Specialization by Coursera
Stanford University and DeepLearning.AI offer a machine learning specialization on Coursera. This beginner-friendly program, created by AI expert Andrew Ng, provides a comprehensive introduction to machine learning. The specialization consists of three courses that cover the fundamental concepts and practical skills needed to build real-world AI applications. This course is perfect for anyone looking to break into the field of AI or enhance their machine-learning skills. With flexible scheduling and hands-on projects, you can learn quickly and apply your knowledge to real-world problems.
Course Details
| Feature | Details |
|---|---|
| Instructor | Andrew Ng and other top instructors from Stanford University |
| Duration | Approximately 2 months (10 hours per week) |
| Learning Format | Online, self-paced with flexible schedule |
| Certificate | Career certificate from Stanford University and DeepLearning.AI |
| Languages | Taught in English with subtitles available in 21 languages |
| Skills Covered | Logistic Regression, Artificial Neural Networks, Linear Regression, Decision Trees, Recommender Systems |
| Tools Covered | Python, NumPy, scikit-learn, TensorFlow |
| Projects | Supervised Learning Models, Neural Networks, Unsupervised Learning Techniques, Recommender Systems |
| Enrollment | Open for anyone interested in learning machine learning |
| Cost | Free to enroll, with the option to purchase a certificate |
| Financial Aid | Available |
Key Features
| Feature | Details |
|---|---|
| Certification | Earn a career certificate from Stanford University and DeepLearning.AI |
| Expert Instructors | Learn from AI visionary Andrew Ng and other top experts |
| Hands-on Learning | Engage in real-world projects and assignments |
| Flexible Learning | Study at your own pace with a flexible schedule |
| Multilingual Support | Subtitles available in 21 languages |
| Career Support | Enhance your resume and LinkedIn profile with a recognized certificate |
Course Curriculum
Course 1: Supervised Machine Learning: Regression and Classification
- Duration: 33 hours
- Content: Build and train supervised learning models for prediction and binary classification tasks, including linear regression and logistic regression.
Course 2: Advanced Learning Algorithms
- Duration: 34 hours
- Content: Learn to build and train neural networks with TensorFlow, decision trees, and tree ensemble methods, including random forests and boosted trees.
Course 3: Unsupervised Learning, Recommenders, Reinforcement Learning
- Duration: 27 hours
- Content: Apply unsupervised learning techniques, including clustering and anomaly detection, and build recommender systems and deep reinforcement learning models.
Projects
| Project | Description |
|---|---|
| Supervised Learning Models | Build and train models for prediction and classification tasks using linear and logistic regression. |
| Neural Networks | Develop and train neural networks for multi-class classification using TensorFlow. |
| Unsupervised Learning Techniques | Implement clustering and anomaly detection algorithms for unsupervised learning tasks. |
| Recommender Systems | Create recommender systems using collaborative filtering and content-based deep learning methods. |
https://www.coursera.org/specializations/machine-learning-introduction
4. Master Machine Learning in Python by GreatLearning
Machine Learning with Python course offered by Great Learning. This course is designed to provide a comprehensive introduction to machine learning using Python, a popular and versatile programming language. You will learn about the key concepts and techniques of machine learning, including supervised and unsupervised learning, and gain hands-on experience through practical projects. This course is ideal for beginners and professionals looking to enhance their skills in machine learning. With expert instruction, real-world projects, and a flexible learning format, you can master machine learning at your own pace.
Course Details
| Feature | Details |
|---|---|
| Instructor | Prof. Mukesh Rao, Adjunct Faculty at Great Lakes |
| Duration | Self-paced learning |
| Learning Format | Online |
| Certificate | Verified Certificate from Great Learning |
| Access | 1 year |
| Course Fee | ₹15,000 (inclusive of GST) |
| Skills Covered | Python Programming, Supervised Learning, Unsupervised Learning, Clustering, Regression |
| Projects | House Price Prediction |
| Prerequisites | Basic knowledge of programming and mathematics |
Key Features
| Feature | Details |
|---|---|
| Certification | Earn a Verified Certificate from Great Learning |
| Expert Instructors | Learn from experienced faculty and industry experts |
| Hands-on Learning | Engage in real-world projects and assignments |
| Flexible Learning | Study at your own pace with access to online content for one year |
| Discussion Support | Access to discussion forums for query resolution |
| Quizzes and Assignments | Test your knowledge with quizzes and assignments |
Course Curriculum
Module 1: Introduction to Machine Learning
- Concepts of Machine Learning and Importance
Module 2: Supervised Learning
- Linear Regression
- Logistic Regression
- Naive Bayes
Module 3: Unsupervised Learning
- Introduction to Clustering
- K-means Clustering
FAQs
| Question | Answer |
|---|---|
| How long can I access the course? | You can access the course content for 1 year. |
| Is the course 100% online and self-paced? | Yes, it is a 100% online learning course that you can learn at your own pace. |
| On what basis are certificates awarded? | Certificates are awarded upon completion of the mandatory course content and satisfactory project submission. |
| Is there forum support? | Yes, you will have access to discussion forums to resolve your queries. |
| Is there a refund policy? | Fees once paid are not refundable. Please make an informed decision before enrolling. |
Target Job Roles
- Machine Learning Specialist
- Data Scientist
- Data Analyst
https://www.mygreatlearning.com/academy/premium/courses/machine-learning-python
5. Introduction to Machine Learning A-Z: AI, Python & R + ChatGPT Prize [2024]
This bestseller course on Udemy, created by two data science experts, is designed to help you master machine learning using both Python and R. Whether you’re a beginner or looking to deepen your understanding, this course provides a thorough and practical approach to learning machine learning algorithms and techniques. With over 1 million students enrolled, this course is trusted worldwide. It includes detailed video lectures, coding exercises, and real-world projects to ensure you not only understand the theory but also gain hands-on experience.
Course Details
| Feature | Details |
|---|---|
| Instructor | Kirill Eremenko, Hadelin de Ponteves |
| Duration | 42.5 hours of on-demand video |
| Learning Format | Online, self-paced |
| Certificate | Certificate of Completion |
| Language | English (with auto subtitles in English, Arabic) |
| Prerequisites | Basic high school level mathematics |
| Skills Covered | Machine Learning Algorithms, Data Preprocessing, Regression, Classification, Clustering, NLP, Deep Learning, Dimensionality Reduction, Model Selection, Reinforcement Learning |
| Tools Covered | Python, R |
| Projects | Multiple real-world projects including predicting house prices, customer segmentation, and more |
| Cost | ₹4,099 (with frequent discounts and a 30-day money-back guarantee) |
| Support | Access to community, Q&A sessions with instructors |
| Additional Resources | 5 coding exercises, 40 articles, 9 downloadable resources |
| Companies Using This Course | Nasdaq, Volkswagen, Box, NetApp, Eventbrite |
Key Features
| Feature | Details |
|---|---|
| Certification | Earn a certificate upon successful completion |
| Expert Instructors | Learn from experienced instructors with industry expertise |
| Hands-on Learning | Engage in practical projects and assignments to apply your knowledge |
| Comprehensive Curriculum | Covers a wide range of machine learning topics, from basics to advanced techniques |
| Flexible Learning | Study at your own pace with lifetime access to course materials |
| Community Access | Join a community of learners and participate in discussion forums |
| Multi-language Support | Course available with subtitles in multiple languages |
Who This Course Is For
- Beginners interested in machine learning
- Students with at least high school level mathematics
- Intermediate learners who want to deepen their knowledge
- Non-coders interested in applying machine learning
- College students aiming for a career in data science
- Data analysts looking to upgrade their skills
- Professionals wanting to transition into data science
- Business professionals aiming to add value with machine learning tools
https://www.udemy.com/course/machinelearning
What is Machine Learning
Machine Learning is like teaching a computer to learn from experience, similar to how humans learn. Imagine you want to teach a computer to recognize different types of fruits. Instead of giving it a list of rules to identify each fruit, you show the computer many pictures of apples, bananas, and oranges, and tell it which fruit is in each picture.
Here’s how it works in simple steps:
- Collect Data: Gather lots of pictures of different fruits and label them correctly (e.g., “apple,” “banana,” “orange”).
- Train the Model: Show these labelled pictures to the computer. The computer looks for patterns and features that help it tell the fruits apart. This process is called training.
- Make Predictions: After training, you show the computer new pictures of fruits it hasn’t seen before. Based on what it learned from the training pictures, the computer tries to guess which fruit is in each new picture.
The more pictures you show the computer, the better it gets at recognizing fruits. This way, the computer “learns” from the data and improves its accuracy over time.
In summary, Machine Learning is all about teaching computers to learn from examples and make decisions based on patterns they recognize without being explicitly programmed with a set of fixed rules.
Why Learn AI and Machine Learning
1. High Demand and Job Growth
The demand for AI and Machine Learning skills is skyrocketing. According to the World Economic Forum, AI is expected to create 97 million new jobs by 2030. This surge is fueled by companies across various sectors, including healthcare, finance, and technology, seeking experts to help leverage data and automate processes.
As industries increasingly adopt AI technologies, the need for skilled professionals continues to grow, making this an opportune time to enter the field.
2. Lucrative Salaries
Professionals with AI and Machine Learning skills are highly valued and well-compensated. The average salary for an AI engineer in the United States is approximately $153,719 per year, while machine learning engineers and data scientists can earn even more, with averages of around $178,515 annually. These high salaries reflect the significant impact and value that AI professionals bring to organizations.
3. Diverse Career Opportunities
AI and Machine Learning open doors to a wide range of career paths. You can work as a Data Scientist, AI Engineer, Machine Learning Researcher, or specialize in areas like Natural Language Processing or Computer Vision. These roles are prevalent in many industries, from tech and automotive to healthcare and entertainment. The versatility of these skills means you can apply them in various contexts, solving different kinds of problems and driving innovation.
4. Impact and Innovation
Working in AI and Machine Learning allows you to be at the forefront of technological innovation. These technologies are driving advancements in personalized medicine, autonomous vehicles, smart cities, and more. By mastering AI and Machine Learning, you become part of a community that’s making a tangible impact on the world. The work you do can lead to significant improvements in various fields, making a difference in people’s lives.
5. Continuous Learning and Growth
The field of AI and Machine Learning is dynamic and ever-evolving. This means there’s always something new to learn, keeping your career exciting and intellectually stimulating. Continuous learning, practical application, and staying up-to-date with advancements are crucial for success in this field. As new technologies and methodologies emerge, you will have the opportunity to continuously expand your knowledge and skills.
6. Future-Proof Your Career
Automation and AI are transforming the job landscape. By acquiring AI and Machine Learning skills, you future-proof your career, ensuring you remain relevant and competitive in an increasingly automated world. Employers are constantly looking for individuals who can help them navigate this technological shift (Learn R, Python & Data Science Online) (365 Data Science). Learning these skills enhances your employability and positions you as a key player in the future workforce.
In conclusion, learning AI and Machine Learning is a strategic move that can significantly boost your career prospects, provide financial rewards, and allow you to contribute to groundbreaking innovations. Whether you’re just starting or looking to advance in your current role, the right course can set you on the path to success.
