Once you’ve decided to learn machine learning, the next important question is deciding how you plan to learn these skills. Most students find guided training helps them learn best. There is no shortage of available options for students to receive guidance in their machine learning training. Read on to learn more about different machine learning training options and what advantages and disadvantages they carry with them.

What is Machine Learning?

Machine learning (ML) is one of the best-known subcategories of artificial intelligence (AI). This complex multidisciplinary field can require training in programming languages like Python, databases like MySQL, and natural language processing (NLP). Common ML careers include Machine Learning Engineers, Data Scientists, and Business Intelligence (BI) Analysts.

Machine learning is often associated with Python programming and data science. Popular uses of ML in daily activities include voice recognition tools like Siri, recommendation lists from Amazon or Netflix, and user engagement icons on platforms like Instagram and TikTok. 

Read more about what machine learning is and why you should learn it.

What Can You Do with Machine Learning Skills?

Machine learning algorithms dominate today’s internet. Websites gather information based on search, social, and shopping. Top ML applications include:

• Social media - Meta Platforms was one of the first well-known companies to use ML to measure user activities. Other social media platforms using ML include Twitter and TikTok.

• Recommendation Engines - If you use Amazon or streaming services, you’ve seen the You May Like feature. Companies like Apple and Netflix use ML algorithms to customize experiences.

• Natural Language Processing (NLP) - Analyzing text includes steps like identifying the language, syntax parsing, and sentiment analysis. Machine learning is essential to NLP.

Why Training Format Matters

Many tech professionals today study machine learning either on-the-job or as part of a broader computer science education. Live online courses, in-person training, and on-demand tutorials are a few of the most popular training formats.

Format matters because students' learning styles can require different training methods. Additional factors include time constraints and budget. Consider taking classes that promote the highest engagement level to get the best training possible.

Types of Training Formats

Machine learning training formats include in-person, live online, on-demand, and free resources. Read on to learn more about the benefits and potential drawbacks of each.

Live In-Person Classes

Traditional in-person training continues to attract machine learning students of all ages. In-person courses provide the highest level of engagement, and the interactive dynamic of the classroom allows students to network with peers and mentors.

If there is any downside to in-person training, it may be a limited number of available local courses in small cities or towns. Beyond this consideration, most students find it worthwhile to travel to class.

Live Online Classes

Live online classes provide engagement comparable to in-person training, and younger students may prefer online learning. Many course providers offer multiple online training options, an essential benefit for those outside major metropolitan areas.

While online classes might not offer the same level of interaction as their in-person counterparts, today's ML students typically appreciate the number of available options.

On-Demand Classes

On-demand classes vary in quality, cost, and length, from short tutorials to programs lasting weeks or months. This training format provides much less engagement or student accountability than in-person or online live coursework.

Still, on-demand classes have their strong points. They can provide appropriate introductory training for machine learning novices, and the shortest seminars often deliver helpful information.

Free Courses

While free learning resources only sometimes offer the same value as on-demand or formal training, they also have their place. Most students begin their machine learning education by watching YouTube videos or scanning online news sites, and free courses are the next logical step.

Free resources include webinars, tutorials, blog posts, and other articles. Consider starting with a short free course if you're not yet ready to commit to a full-length training program.

Depth of Training Formats

The length and depth of machine learning training formats vary by provider, type, and level of difficulty. Read on to learn more about the depth of ML training methods. 

Certificate Programs

Certificate programs run from a few weeks to months. They typically provide the most depth of training next to college or university degree programs.

Many certificates are composed of multiple training bootcamps. For example, Noble Desktop offers a Python Machine Learning Bootcamp, but you can save by taking it as part of their Data Analytics Certificate program.

Training Bootcamps

Training bootcamps for machine learning often include related topics like Python, automation, or data visualization. Some ML bootcamps focus on development, while others focus on data science.

Noble Desktop offers multiple machine learning bootcamps, including an immersive Python Machine Learning Bootcamp. Check course listings for more details.

Introductory Courses

You might begin machine learning training through videos, including seminars and tutorials. Check out free machine learning resources and tutorials from Noble Desktop, or visit their YouTube channel for more.

Whether you plan to be a Machine Learning Engineer or a Business Analyst, you can get valuable training through the Classes Near Me tool and other online sources.

Learn Machine Learning Skills with Noble Desktop

Noble Desktop offers in-person and live online bootcamps and certificates featuring machine learning (ML), like:

• Data Science Certificate - This program provides data science fundamentals before advancing through ML, Python for automation, and Structured Query Language (SQL).

• Python Machine Learning Bootcamp - Programmers already comfortable with Python data science can save by taking this bootcamp as part of the Data Science Certificate.

• Python Data Science & Machine Learning Bootcamp - This bootcamp combines ML and Python training modules from the Data Science Certificate but without the SQL bootcamp. 

• Check out Noble Desktop's full-time and part-time data science programs here.

Key Takeaways

• Machine learning (ML) is one of the best-known subcategories of artificial intelligence (AI).

• ML training can include related topics like Python, MySQL, and natural language processing (NLP).

• Top careers for ML include:
  • Machine Learning Engineer
  • Data Scientist
  • Business Intelligence (BI) Analyst

• Top machine learning applications include:
  • Social media
  • Product recommendations
  • Natural language processing (NLP)

• Training formats for machine learning include:
  • In-person courses
  • Live online training
  • On-demand classes
  • Free webinars and tutorials

• Top options for getting in-depth training include:
  • Certificate programs
  • Training bootcamps
  • Formal degree programs

• You can receive comprehensive machine learning training through Noble Desktop, either in person or online. Top programs include:
  • Data Analytics Certificate
  • Python Data Science & Machine Learning Bootcamp
  • Python Machine Learning Bootcamp