How Long Does it Take to Learn Machine Learning?

Like many aspiring data professionals, you might want to learn machine learning but worry that it will take too much time. It’s understandable. Machine learning is a complex, multidisciplinary field, and different roles require different levels of knowledge and skills. It can take a Machine Learning Engineer longer to learn their job requirements than a Business Analyst or Data Analyst, but experts agree it takes at least six months to master the basics.

Of course, this depends on several factors. Keep reading to learn about how you can learn machine learning and some resources to speed the process along.

What is Machine Learning?

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

Machine learning is often associated with Python programming and data science. Supervised, unsupervised, and reinforcement learning are the top three models of ML algorithms. 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?

Machine learning algorithms dominate today’s internet. Websites gather information based on everything you do online, from your search patterns to previous purchases, social media posts, and whether or not you abandon a product in a cart. As ML algorithms continue to influence our personal and professional lives, more and more businesses use them to streamline processes and determine customer and client journeys. The following are a few of the most popular machine learning applications.

• Social media - Meta Platforms (formerly Facebook) was one of the first well-known companies to use ML to measure user activities. Examples of how they analyze statistical activity include their user engagement, chatbots, and content filtering features. Other top social media platforms using ML extensively include Twitter, Pinterest, and TikTok.

• Product Recommendations - If you’ve ever bought a product from Amazon or subscribed to a streaming service, you’ve probably seen the You May Like feature. Companies ranging from Apple to Netflix use machine learning algorithms to customize your experience.

• Natural Language Processing (NLP) involves text analytics and functions combined with machine learning. Analyzing text includes basic steps like identifying the language and more complex steps like syntax parsing and sentiment analysis. ML is essential to text analytics and NLP solutions.

Average Time it Takes to Learn Machine Learning

The average machine learning curriculum runs around six months, although it can take years to master multiple requirements for a specific role. Not everyone has the same ML career path, so consider your own experience and skill set. For example, a beginner might need training in Python programming fundamentals, whereas an experienced programmer might be able to dive straight into a machine learning bootcamp. Some students will attend bootcamps to learn from the ground up, while others have on-the-job experience but want to transition from one career to another.

Primary factors that influence how long it will take you to learn ML include:

• Your previous data science or data analysis experience, if any
• How many hours each day your ML training requires
• The type of training (self-taught, on-demand, bootcamp or certificate programs)

Machine learning trainees with previous programming experience may have an advantage over those with none, and students who excel in statistics or probability can also expect an easier time.

Other Factors

If you’re starting a machine learning career, your level of knowledge and experience can differ from that of many of your fellow students. Consider what complementary skills and knowledge you bring to the table, especially in data visualization, algorithms, and how ML applies to everyday activities.

Availability/Pace of Training

Your current schedule has a measurable effect on your ability to learn ML within a particular timeframe. While students fresh out of high school may have 40 hours a week to devote to machine learning, busy professionals and those with family obligations may only be able to study part-time. For example, you can complete Noble Desktop’s Python Machine Learning Bootcamp in months or even weeks, whereas the comprehensive Data Science Certificate takes more than twice as long.

Overall Goal

One student’s goal for mastering machine learning can differ widely from another’s. Some want to train for a specific position like Machine Learning Engineer. Others choose to add ML to an existing skillset that includes Python programming, data analysis, or business intelligence analysis. Besides the time available to you and the skills you bring to the table, your goal for ML training will be one of the most important factors affecting how long it takes you to reach it.

Career Transition

This factor only applies to those already in a data-centered field. The transition from Data Analyst to a Data Scientist role can be relatively smooth, as can that of a Machine Learning Researcher to Machine Learning Engineer. If you currently have a position like one of these and want to move into a more ML-centered role, consider targeted training like Noble Desktop’s Python Data Science and Machine Learning Bootcamp or Python Machine Learning Bootcamp. Check course listings thoroughly to find the most appropriate course for you.

Level of Difficulty, Prerequisites, & Cost 

Studying machine learning (ML) can be a lifelong pursuit. The challenges of learning this topic depend on how much you need to learn and where you will apply it. 

You may have more challenges learning ML if you lack experience with algorithms or have little familiarity with programming languages like Python. Consider learning these through a course that features them or includes them as part of a broader computer or data science curriculum.

Machine learning training costs range from free to around about $1,895 to $4,495 for a bootcamp or certificate program. Some of these courses include intensive ML training and can be completed in a few months or weeks.

Read about how difficult it is to learn machine learning.

Watch a Free Machine Learning Course Online

Not ready to take a full-length machine learning course? If you’re not able to commit to a full-length bootcamp or certificate, you should consider the many free online resources you can use to start studying machine learning.

One of the most important areas of study for those new to machine learning is technical proficiency in a free programming language like Python. If you don’t already have Python experience, it can be helpful to learn more about it before you dive into the study of machine learning. 

Noble Desktop hosts an online seminar entitled Intro to Python Fundamentals. In this free introductory course, you’ll learn about the practical uses of Python. The curriculum walks new programmers through every step to get started in Python programming—from how to install Python to how to write code.

Other free online courses include Introduction to Embedded Machine Learning from Edge Impulse, Artificial Intelligence: Ethics & Societal Challenges from Lund University, and the University of London’s Foundations of Data Science: K-Means Clustering in Python.

Read about more free machine learning videos and online tutorials.

Learn Machine Learning with Hands-on Training at Noble Desktop

Noble Desktop offers a variety of bootcamps and certificates that feature machine learning, both in-person and live online via teleconferencing. Some include Python as a focus, others include machine learning as part of a broader data science curriculum, and others cover ML in a FinTech curriculum. All bootcamps and certificate programs feature small class sizes to maximize personal attention from expert instructors.

• Data Science Certificate - Noble’s Data Science Certificate program teaches participants data science fundamentals before advancing through machine learning, Python for automation, and Structured Query Language (SQL). This immersive certificate is open to beginners; you can retake it for up to one year at no additional charge.

• Python Machine Learning Bootcamp - Programmers already comfortable with Python and its data science libraries can get their machine learning training as part of the Python Machine Learning Bootcamp. Attendees can save by taking this shorter course as part of the Data Science Certificate program.

• Python Data Science & Machine Learning Bootcamp - This comprehensive bootcamp combines the same ML and Python training modules as the Data Science Certificate but does not include the Structured Query Language (SQL) bootcamp. It’s open to beginners and designed to prepare students for entry-level Python engineering or data science positions. 

For more information on Noble Desktop’s data science classes, including machine learning, check out all their full-time and part-time data science programs.

Key Insights

• Machine learning (ML) is a complex, multidisciplinary field.
• Different roles demand different levels of knowledge and skills. Top careers which differ in required skill sets include:
• Data Scientist
• Machine Learning Engineer
• Business Intelligence (BI) Analyst
• Data Analyst
• Experts agree it takes six months or more to master ML basics.
• Top skills for machine learning pros include programming languages like Python and R, databases like MySQL, and natural language processing (NLP).
• Factors like your previous experience and professional goals will influence how long your specific ML training will take.
• Many analysis professionals want to deepen their machine learning skills to transition to roles like Data Scientist or Machine Learning Engineer.
• You can get a comprehensive machine learning education through an in-person or live online course with Noble Desktop.