How to Learn Machine Learning Online in the US: Best Platforms & Study Tips

Machine learning (ML) is transforming industries across the United States and worldwide. Statistics by the U.S. Bureau of Labor show a 35% growth in jobs for data scientists and ML specialists projected from 2023 to 2033. With the number of platforms offering online machine learning courses and certifications surging, pursuing ML from reputable institutions globally has become easy.

In this article, let’s discuss how learners in the US can gain proficiency in machine learning through the best online platforms to upskill and tap into this booming field. 

Also Read: Online Machine Learning Courses for Working Professionals

Top 5 Best Platforms to Learn Machine Learning Online

In the present era, machine learning is a key skill for growing in the tech-driven world, and it opens opportunities for professionals to take their careers to the next level. An online program in machine learning allows busy professionals and students with the flexibility to complete the course at their own pace.

Here are five of the best platforms where you can start or advance your machine learning journey.

upGrad

upGrad is South Asia’s largest EdTech platform, enabling professionals to upskill online without pausing their careers. It offers many undergraduate and postgraduate programs, including online machine learning degrees and certifications in partnership with top Indian and international universities and institutions to make online learning as engaging and effective as traditional classroom lessons.

Notable features:

• Globally recognized university partnerships.
• Immersive learning experience.
• Global alumni and peer network.
• Flexible online learning with live sessions.
• Industry-relevant curriculum co-designed by experts.
• Career support for U.S. and global markets.
• Generative AI integrated modules, tools, and projects.
• Personalized 1:1 coaching.
• Daily doubt resolution support to keep you on track.
• Accredited and recognized courses.
• 4 incredible ML programs and certifications from top institutions are available to choose from.

Google AI

Google’s fast-paced and practical introduction to machine learning through its “ML Crash Course” features short videos, interactive visuals, and practical exercises to help you learn by doing hands-on exercises. The platform offers free tutorials, guides, and TensorFlow-based courses. It’s ideal for developers who want to learn directly from a tech giant like Google.

Notable features:

• Powerful tools and innovative applications.
• Global technology leader.
• Innovation and research-focused.
• Diverse product portfolio.
• Strong corporate culture.
• Global reach.

Fast.ai

Another popular learning platform, Fast.ai, offers an “Introduction to Machine Learning for Coders.” This course helps learners quickly start building real machine learning models using PyTorch. It is best for individuals with experience who want a hands-on, code-focused way to learn.

Notable Features:

• Integration with PyTorch.
• Three-tiered API structure.
• Specialized modules for various domains.
• Efficient data handling with DataBlock API.
• Advanced training techniques.

DataCamp

Datacamp’s machine learning courses teach how computers can learn from data and make smart decisions independently. The course helps you learn valuable skills like deep learning, natural language processing, and managing ML projects. It’s ideal for hands-on learners and is not degree-focused.

Notable Features:

• Hands-on learning.
• Beginner-friendly.
• Structured learning paths.
• Real-world projects.
• Expert instructors.

GitHub

GitHub presents a 12-week ML course with 26 lessons that teach the basics of machine learning through traditional ML methods. The course also explains how ML can help computers make smart decisions from data. GitHub shares many ML learning paths and tutorials freely by AI practitioners.

Notable Features:

• Version control with Git.
• Collaboration tools.
• Open source hosting.
• GitHub Copilot

Study Tips for Online Machine Learning Courses

Whether you are a busy working professional or a student with commitments and responsibilities, online machine learning courses are your best alternatives for a rewarding career in AI and ML. These courses offer complete flexibility and serve the best purpose of busy individuals seeking upskilling. However, learners must stay motivated to complete the course per their schedule. The following tips will keep learners motivated while pursuing online machine learning courses:

Realistic study goals

Realistic goals are crucial for breaking down the curriculum and achieving the desired milestone. Learners may set achievable weekly or monthly milestones and track progress for effective results.

Consistent schedule

Learners must create and follow a consistent study schedule, dedicating fixed hours every day/week. This will help build a learning habit and keep you on track with your study goals. 5-7 hours per week of consistent studies can also be effective.

Engage actively

To stay focused or engaged, learners can take notes between video lectures or pause the videos to reflect on important points discussed. They can also attempt quizzes and assignments and find other ways to engage with what is being taught.

Leveraging online forums and communities

Online forums like Reddit and Stack Overflow, as well as other course-specific forums, can be leveraged to ask questions, share insights, and learn from peers.

Practicing coding and ML algorithms

Hands-on practice is crucial in any technical domain to apply your skills in practice. Hence, learners can use tools like Jupyter Notebook, Google Colab, or Kaggle to apply their skills and get hands-on experience.

Also Read: AI vs Machine Learning: What’s the Difference?

What are the Career Prospects in Machine Learning in the US?

The U.S. Bureau of Labor Statistics projects 26% growth in jobs for computer and information research scientists from 2023 to 2033, making machine learning a sought-after area to pursue a career.

As the US continues to lead the global AI/ML growth at scale, the industry is experiencing a robust surge in demand for professionals with ML skills.

Here’s a list of industries hiring ML professionals in the US:

• Technology and Software
• Healthcare and Biotech
• Finance and FinTech
• Retail and E-commerce
• Automotive
• Manufacturing
• Cybersecurity
• EdTech
• Legal

These industries seek ML professionals in the US for different job roles, shown in the table below, along with their average annual salary:

Also Read: How to Become a Machine Learning Engineer with a Master’s Degree

Skills and Prerequisites for Learning Machine Learning in the US

To learn Machine Learning, get started with foundational courses for skill building. Follow the steps below to begin your journey:

1. Start with beginner-friendly courses covering Python, statistics, and basic data handling.
2. Understand core ML concepts, like supervised vs. unsupervised learning, model training, and algorithms.
3.  Use different platforms to practice with real datasets and apply the acquired skills.
4. Once comfortable with the basics, dive deep and explore advanced topics.
5. Build a portfolio by adding the projects you worked on.
6. Join communities to stay updated, participate in online forums, and attend virtual workshops or webinars.

Also Read: Explainable AI: Making Machine Learning Models Transparent

How can upGrad help you?

Working professionals in the US can boost their careers with online AI and Machine Learning courses through upGrad to enhance employability and gain industry-relevant skills. These flexible online courses are designed in collaboration with top universities to equip learners with hands-on experience and career support to thrive in the tech-driven job market.

Some popular Machine Learning AI programs available on upGrad:

• Post Graduate Certificate in Generative AI (E-Learning)
• Master of Science in Machine Learning & AI
• Executive Certificate in Generative AI for Leaders (E-Learning)
• Executive Diploma in Machine Learning and AI with IIIT-B

For more information, email globaladmissions@upgrad.com or call +1 (240) 719- 6120.

FAQs on How to Learn Machine Learning Online in the US

Q: What is the best way to start learning ML online as a beginner?
If you are a beginner at ML, start your journey with a foundational course teaching Python, basic statistics, and linear algebra. upGrad offers beginner-friendly programs to help you build skills through structured content and hands-on projects.

Q: Do I need a background in programming for machine learning?
Ans: A background in programming does help in ML courses. However, many online machine learning courses for beginners start from scratch to teach from the basics. A foundation course in Python, alongside learning machine learning concepts, can serve as an effective path.

Q: Are online machine learning certificates valuable for US-based job roles?
Ans: Yes, certificates from recognized platforms are valuable with practical project work. Recruiters value hands-on experience and industry-relevant skills over educational credentials.

Q: How long does it take to learn machine learning online?
Ans: The duration of learning ML online can vary depending on the commitment level and prior experience of learners. Beginners might take 6–12 months to become proficient with a consistent schedule of 5 to 10 hours of study per week.

Q: Which online platforms offer student support after completing machine learning courses?
Ans: upGrad is a renowned online learning platform offering guidance and support on courses, university admissions, visa processing, and more.

Q: Can I transition into a machine learning role from a non-tech background?
Ans: Yes, transitioning to machine learning roles from a non-tech background is possible by upskilling in programming, data analysis, and ML frameworks. Start with foundational courses and build a portfolio gradually to establish your capabilities.