Image courtesy of the author
We all know that finding the right course can be a daunting task. The team at KDnuggets has teamed up to create this blog so you don't have to do the work. We've done it for you!
The world is moving fast. Really fast. The use of technology in 2024 is showing the world how it can improve workflows, the medical industry, the financial sector, and more. Perhaps you are interested or have been wanting to join this community.
If you're considering entering the machine learning industry and are ready to take the next step towards certification, read on.
Machine Learning Specialization
Link: Machine Learning Specialization
Level: Beginner
Duration: 2 months at 10 hours per week
A three-course program from AI visionary Andrew Ng designed to help students master foundational AI concepts and gain practical machine learning (ML) skills, including building and training machine learning models.
You will learn how to build ML models using NumPy and scikit-learn, how to build and train supervised models for prediction and binary classification tasks, how to build and train neural networks using TensorFlow to perform multi-class classification, and how to build and use decision trees and tree ensemble methods.
We apply these best practices to ML development, using unsupervised learning techniques for unsupervised learning such as clustering and anomaly detection, building recommendation systems using collaborative filtering approaches and content-based deep learning methods, and building deep reinforcement learning models.
IBM Machine Learning Professional Certification
Link: IBM Machine Learning Professional Certification
Level: Intermediate
Duration: 3 months, 10 hours per week
IBM's six-course online education program equips students with practical ML skills including supervised learning, unsupervised learning, neural networks, and deep learning, and upon completion of the six courses, students will receive a professional certificate from IBM and Coursera.
In this course, you will learn how to acquire the latest practical skills and knowledge used by machine learning professionals in their daily work, how to create a recommendation system in Python to compare and contrast different machine learning algorithms, gain working knowledge of KNN, PCA, and non-negative matrix collaborative filtering, and predict course ratings by training a neural network and building regression and classification models.
Google Professional Machine Learning Engineer Certification
Link: Google Professional Machine Learning Engineer Certification
Level: Beginner
Duration: Approximately 2 hours
You will use Google Cloud to design, build, and create machine learning models. In this course, you will work with large, complex datasets, write repeatable, reusable code, and consider responsible AI and fairness throughout the ML model development process, working closely with other functions to ensure the long-term success of ML-based applications.
To earn the certification, you must take and pass a two-hour exam consisting of 50-60 multiple-choice questions covering topics such as framing ML problems, designing ML solutions, and developing ML models.
Machine Learning Specialization
Link: Machine Learning Specialization
Level: Intermediate
Duration: 2 months at 10 hours per week
The University of Washington's Machine Learning Specialization is a four-course online educational program that covers the key areas of machine learning, including prediction, classification, clustering, and information retrieval. In this course, you will analyze large, complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data.
Upon successful completion of the course, you will receive a shareable certificate that you can attach to your resume to communicate your knowledge and skill set to potential employers.
End-to-end machine learning
Link: End-to-End Machine Learning
Level: Intermediate
Duration: 4 hours
If you are interested in how the machine learning model process works from start to finish, check out this course offered by DataCamps.
In this comprehensive course, you'll learn in depth how to design, train, and deploy end-to-end models. Through compelling real-world examples and hands-on exercises, you'll learn how to tackle complex data problems and build powerful ML models. By the end of this course, you'll have the skills you need to create, monitor, and maintain high-performance models that deliver actionable insights.
summary
Skill up with these top machine learning courses for a fraction of the cost of college tuition. Education and skilling doesn't have to be expensive – just take the courses that are right for you.
Nisha Arya Nisha is a Data Scientist, Freelance Technical Writer, Editor & Community Manager at KDnuggets. She is particularly interested in providing data science career advice, tutorials and theory-based knowledge on data science. Nisha covers a wide range of topics and loves to explore the different ways in which artificial intelligence can help extend human lifespan. An avid learner, Nisha hopes to mentor others while expanding her technical knowledge and writing skills.
