Switch Your Career to Machine Learning – A Complete Guide

Machine Learning is currently the hottest career around and its popularity is only increasing! Currently, Machine Learning Engineer ranks The Best Job of 2019 with a 344% market growth and an average base salary of around $145,000 per year. And Machine Learning is also impacting almost all other industries like Quantum Computing, Healthcare, Finance, Robotics, Agriculture, etc.

Keeping all this in mind, learning Machine Learning can improve your career prospects enormously. This field will help you in reskilling yourself and learning cutting edge technologies that will only help you in this competitive job market. And it doesn’t hurt that Machine Learning is also a fascinating subject to learn. Smart robots, artificial neural networks, natural language processing, who wouldn’t want to know more about such interesting topics?!!

Switch-Your-Career-to-Machine-Learning-A-Complete-Guide



And that is the reason this article deals with learning Machine Learning and the method to eventually switch your career to this field. First, we will focus on the prerequisites required to start learning ML and then the resources you can use for further learning. Read on to find more!

How To Start Learning Machine Learning?

While starting Machine Learning, there is a roadmap you can follow, especially if you are currently in another job and want to switch. After you have some knowledge of ML, you can continue as you think best and acquire more in-depth knowledge. So, here is some basic information on How To Start Learning Machine Learning.

1. Prerequisites

There are some prerequisites that you need to know before officially starting Machine Learning! So it’s best that you study these first along with your current career and then start learning more about ML when you have some idea of these prerequisites. Now, let’s see them!

(a) Linear Algebra and Multivariate Calculus: Both Linear Algebra and Multivariate Calculus are important in Machine Learning. If you are planning on moving into application heavy machine learning, then you don’t need to be that focused on maths as there are many common libraries available. But if you want to shift into R&D in machine learning, then mastery of Linear Algebra and Multivariate Calculus is very important as you will have to implement many ML algorithms from scratch.

(b)Statistics: Data plays a huge role in Machine Learning. In fact, around 80% of your time as an ML expert will be spent collecting and cleaning data. And statistics is a field that handles the collection, analysis, and presentation of data. So it is no surprise that you need to learn it!!! Some of the key concepts in statistics that are important are Statistical Significance, Probability Distributions, Hypothesis Testing, Regression, Bayesian Thinking, etc.

(c) Python: While there are other languages you can use for Machine Learning like R, Scala, etc. Python is currently the most popular language for ML. In fact, there are many Python libraries that are specifically useful for Artificial Intelligence and Machine Learning such as Keras, TensorFlow, Scikit-learn, etc. So if you want to learn ML, it’s best if you learn Python! You can do that using various online resources and courses such as Fork Python available Free on GeeksforGeeks.

2. Machine Learning Resources

Now that you know enough about the Machine Learning prerequisites, you can actually focus on learning the subject. Since you are actually switching your career, there are multiple ways of getting the necessary knowledge to apply for ML jobs. Let’s see these now.

(a) University Education: If you want to be completely and formally prepared for a career in Machine Learning, then a University Education is the way to go. An education from a top university will be very helpful in providing you a platform to apply for Machine Learning jobs, especially since you are switching your career. So a degree will provide some credibility that you actually know Machine Learning and are industry-ready.

However, one drawback of getting a University Education is that it is insanely expensive. Chances are that you already went to university for your current career and the cost of a fresh university education could finish your savings or even put you into debt. So only opt for a University Education if you can afford it and you think you need more formal support to switch your career.

(b) Free Online Courses: In case you don’t want to go to university again, you can always opt for a free Machine Learning online course. This will mean that you can learn ML on your own schedule along with your current job and then switch when you are ready. There are many platforms these days from where you can learn Machine Learning for free such as Coursera, Udemy, Edx, Udacity, etc.


But there is a drawback of free online courses as well. These courses provide you the basic information you need to know in order to get started but they don’t go into much depth. Also, there is not much support in case of doubts or problems while studying.

Do you think that neither of these options appeals to you? Fear not, there is a third option as well! GeeksforGeeks has created a course that provides the thorough education and credibility of university courses without the insane fees. A course that also provides doubt support, unlike many free online courses. Are you interested? Then check this out!

Machine Learning Foundation With Python

Machine Learning Foundation With Python is the perfect place for beginners like you to start your journey of Machine Learning. In this course, you will learn the core idea of ML, which is to create systems that have the ability to automatically learn from data without being explicitly programmed. You will learn about key concepts of Machine Learning, effective machine learning techniques, and gain practice implementing them and getting them to work for yourself all in a classroom program. This course is specially scheduled on weekends so that you can learn alongside your current job and make the career switch into Machine Learning when you think you are ready.

Note: You should know the basics of any one programming language among C, C++, Java or Python to get started with this course.

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Course Features:

  • Training Certificate
  • Course mentored by Industry experts having hands-on experience in ML-based industry projects.
  • Internship Opportunities at GeeksforGeeks
  • Project-based learning which will add stars to your resume
  • 4 projects based on real-world applications which include 1 Major Project and 3 Minor Projects

Are you interested? Well, then REGISTER NOW because this course starts on 21 December 2019. Also, this course is priced at INR 17,999 but it is available at an Early Bird Offer price of INR 10,999.

You are just a click away to begin the journey to your dream job in Machine Learning. Register now for the Machine Learning Foundation With Python course by clicking on the button below.

Machine Learning Foundation With Python



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