What is the Fastest Way to Learn Machine Learning?

In the last decade, artificial intelligence has had a large influence on the field of technology. Machine learning is a valuable and relevant skill for not only those joining the AI sector but also anyone who wants to join a field that regularly uses machinery. That includes industries such as finance, healthcare, manufacturing, automotive, and even entertainment. Machine learning is used to automate tasks, provide recommendation systems, and even help with predictive analytics. There are many ways to learn machine learning, but which way is the fastest and most efficient? To answer that question, it’s important to consider a few things, including your proficiency, the class format, and your overall educational goals. This article takes a closer look at the different types of machine learning courses, and which ones work best based on your skill level.

Introductory Skills

For beginners in machine learning, there is fundamental information that you must learn before diving into the world of artificial intelligence. You will gain a basic understanding of machine learning concepts and terminology at this level. Python is a go-to programming language for machine learning, and many early-level courses will offer some review. Introductory skills also include algorithms in this field, and how they can be used to create efficient machine learning systems.

One-Day Classes

One-day classes are the perfect way to quickly pick up machine learning basics. This is a good idea for those with limited experience in the subject. It’s also a great option for those unsure of if they want to take the plunge and commit to a full course. Seminars, webinars, and workshops may all be promoted as one-day courses, so it’s important when registering that you check the time commitment, as these classes may go anywhere from a few hours to a full working day. For beginners, this course type is ideal, and one of the best ways to learn the basics of machine learning at an introductory level.

Workshops

Workshops are one or multi-day learning opportunities that offer hands-on experience with fundamental machine-learning techniques. Because workshops are shorter than traditional courses, they are likely to focus on specific parts of the machine learning process. For example, there may be workshops dedicated to algorithms, programming, or task automation. Though workshops may be tailored towards any proficiency, they can easily be found at the beginner level for fundamental topics.

Free Online Courses

Free online courses hold a lot of appeal for those who want access to machine learning courses at little to no cost. This is especially relevant for those who want to learn more about machine learning at a self-paced schedule, with minimal fees. Free online courses are a great place to network and learn more about resources created by the community, but they are often lacking in professional-level resources. Because of this, free online courses are great for beginners, and a great way to learn introductory skills for those who are on a budget, or waiting to commit to a full course until they are more familiar with the content. 

Intermediate Skills

At the intermediate level, you will become more confident in your basic machine-learning skills. Many courses will review algorithms and programming. They will also introduce machine learning libraries, data cleaning, and model evaluation. Though certain courses will work on deep learning and neural networks, some save those for their advanced-level courses. Professional skills at this level can help you transition to the workforce.

Bootcamps

Bootcamps are an intensive learning opportunity that will help turn theory into practice. These programs typically last 8-12 weeks, though this timeline will change depending on if the course is full-time or part-time. Many bootcamps focus specifically on professional skills or real-world applications with the help of project-based learning. Machine learning bootcamps are a fast way for intermediate learners to grow their skills while also preparing for a job in the field. Once you have grown your basic skills in machine learning, bootcamps become a highly recommended next step for continuing your education, as they are efficient and effective. 

On-Demand Learning Platforms

On-demand learning platforms refer to websites that offer lessons that are accessible at any time. Udemy, Coursera, Skillshare, and other related platforms offer flexible, self-paced courses that can help you learn machine learning. They are offered online and include video lectures, interactive quizzes, learning modules, and other hands-on activities. On-demand learning platforms are offered at any proficiency level, but those with intermediate skills may find them particularly useful for reviewing concepts and transitioning into higher-level courses. They also function as a great method for maintaining your machine learning skills during a break.

Advanced Skills

The advanced level of machine learning is all about mastering the introductory and intermediate skills so that they can be built on. This includes mastery of deep learning techniques and implementation of advanced machine learning models. Being closely related to data science, many machine learning courses will also introduce concepts like natural language processing and data modeling. This is also the proficiency level where instructors will use new technologies and advancements in machine learning to help you evolve as a learner. At this level, it is highly recommended that you choose courses based on the curriculum and the expertise of the instructors. This is to ensure that they both align with your overall educational and career goals.

Professional Training Courses

Professional training courses are ideal for advanced-level learners because they offer both in-depth and practical knowledge. They are tailored towards professionals and can offer guidance and career assistance along the way. Professional training courses can be more expensive but may offer workshops, seminars, intensive training sessions, and other valuable resources that can provide a comprehensive learning experience. These training courses are also great for mentorship and networking in the field of machine learning. Having mentors is one of the quickest ways to grow in your machine learning and overall professional skills at higher levels.

Certificate Programs

Certificate programs offer a structured curriculum that can act as an endorsement of your skills. This can lead to additional job opportunities once you’ve graduated. Certificate programs will teach advanced concepts in preparation for the test you will need to take to become certified. This is the fastest method for those who want to amplify their advanced skills and become proficient in the most important information without too much padding from the other machine learning concepts. If you take a certificate program, you will have a recognized credential upon completion. 

Learn Machine Learning with Noble Desktop

Noble Desktop is a great place to start if you’re looking to learn machine learning. They have a Classes Near Me tool that lines up all available courses and allows you to easily compare them. They also host their own classes. Their general Python Data Science & Machine Learning Bootcamp teaches Python as it relates to data analysis, machine learning, and automation. Python is a common programming language in artificial intelligence which makes it a valuable asset in the field of technology. This specific class is two bootcamps packed into one. The curriculum covers Python for automation, data visualization, and interactive dashboards. This comprehensive course will build your confidence in programming so that you’re not only ready for entry-level positions in data science and Python engineering, but capable of creating predictive models from data, and automating everyday tasks.

For those who want a more streamlined learning experience, Python for Machine Learning is one option. The course starts with fundamental concepts like regression analysis, classification, and decision trees. You’ll use the Pandas library to clean and balance data, apply machine learning algorithms, and pick up other important theoretical concepts, such as overfitting, variance, and bias. The course ends with a final portfolio project that helps turn theory into practice. Since you must be familiar with Python and a few data science libraries to comfortably take these courses, it is recommended that you join Noble Desktop’s Python Programming Bootcamp if you are unfamiliar. You can gain programming essentials that will allow you to comfortably manage your new machine-learning skills.

There is also the option of taking an artificial intelligence course, specifically Noble Desktop’s Generative AI with ChatGPT. This class covers AI in a fun and exciting way. This is a great way to see machine learning in action. ChatGPT is more relevant these days than ever, and this is your opportunity to contribute to one of this decade’s more popular artificial helpers. Through this course, you’ll learn how to write prompts in a way that generates helpful responses.