How to Kick Start Your Career in Machine Learning
Machine Learning is one of the hottest career paths of today. It’s talked about everywhere you go- the web, in print, or even in interviews. You probably use spin-off technology based on ML every day without even realizing it. Wondering what it’s all about? Here’s the perfect guide to understanding if ML is for you and to kick start your Machine Learning career.
What is Machine Learning?
Machine Learning is the art and science of building self-improving models and algorithms for computers to automate or aid human decision making and produce accurate predictions and classifications. A simple example would be your Google Assistant or Amazon Alexa which uses ML to develop an AI that learns to synchronize your mail and schedule according to your working patterns. Or Facebook or Hike’s chatbots which learn conversation patterns gradually.
Machine Learning is widely used across all industries today right from quantitative trading at trading benches, to understanding customer decisions and advertisement reach for e-commerce giants. The basic process involves processing and feeding a vast amount of data which is used to ‘train’ the algorithms to produce more accurate predictions.
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Machine Learning algorithms by and large are divided into two ‘types’- ‘supervised’ and ‘unsupervised’. Supervised learning is one wherein labels are already present and the job is simply to predict the most accurate output based on a given input. On the other hand, unsupervised learning is a beast of its own as it involves attempts to make sense of data by various clustering and classification algorithms.
Career in Machine Learning – The Machine Learning Job Market
People well versed in the nuances of ML algorithms can find a plethora of options due to the deep proliferation of computing techniques and the requirement to process and make decisions based on a large amount of data. An entry-level position as an ML engineer typically pays around 7.5 LPA with most preferred choices for employment being- banks, consulting companies, the big four of tech- Facebook, Google, Amazon, and Apple.
Candidates typically are from a technical background with strong programming skills and experience in data handling through languages high-level languages such as Python, R, and Scala with various frameworks such as Keras, Tensorflow, etc. Along with it, strong quantitative aptitude and knowledge of statistics and mathematics of calculus, linear algebra is required for better decision making. So Machine Learning as a career has its challenges but also rewards suitably
Career in Machine Learning – Typical Background for an ML Engineer
Machine Learning engineers come from quant heavy fields such as engineering, operations research, statistics, etc with strong programming skills in languages such as Python, R, and Scala. Additionally, experience in database management through SQL and the use of various Excel functions also help.
Most recruits are engineers from Computer Science, IT, and other circuital branches such as ECE, EEE, EIE. However, other technical majors such as those studying computer applications, bachelor of science too get their opportunities. A candidate must display the ability to think quickly and recognize patterns and make decisions based on processed data.
Not from a technical background? No worries! You can still go ahead for diploma courses from sites such as UpGrad, DataCamp, Udemy and launch your ML career.
Career in Machine Learning – Few Courses You Can pursue
First, let me tackle the issue of programming. If you are uncomfortable with programming, taking basic courses in Python or R through DataCamp, Codecademy, or YouTube tutorials would do well. MIT OCW runs a fantastic series titled- Introduction to Computer Science and Programming in Python. Great Lakes’ courses and YouTube sessions on Python, ML, and Statistics once again offer a wonderful insight into whether the world of ML and AI is for you. Even if not that comfortable with numbers, one has to understand how various statistical methods work and how to use each of them. These skills form the basic foundation on which
Based on different levels of education you could start your journey through various online courses. Among them, the most famous ones include the Data Science and Machine Learning tracks on sites such as DataCamp. However, before you begin it is always better to get a basic grasp on mathematical topics such as Calculus, Linear Algebra, Set Theory, and Vector Calculus. DataCamp’s vast array of courses could be taken both by school students as well as college grads or someone looking for a career transition. For reviewing mathematics once again there are plenty of resources on YouTube such as NPTEL courses or even MIT OCW’s course on Linear Algebra by Gilbert Strang.
If you’re a little more serious about it, you Udemy and Coursera have several courses on Machine Learning, ranging from Andrew Ng’s classic Machine Learning course which teaches you in-depth both- the underlying theory and applications to more practically geared ones such as those by the University of Michigan on Applied Machine Learning. On Udemy you have courses taught directly by ML engineers working for the likes of Amazon, Facebook, and other industry giants.
For professional certificate courses to be taken along with or after your undergraduate a few names that pop up are- Great Lakes Learning, Imarticus Learning, and UpGrad. These courses can be taken online and offer a thorough mix of both theory and application leaving you with an industry-recognized certificate.
Among the elite institutions, IIIT-Hyderabad runs an Advance Certificate on AI/ML for Working professionals. The program has been well received and has got a pat at the back from Analytics India. This course can not only be taken by freshers but also by people looking to boost or switch careers. Nearly 70% of the class consists of people with 5 years of work experience. IIM Bangalore runs a short certificate on Machine Learning with Business Applications. IIM Kozhikode also has an Executive Management Programme in Artificial Intelligence & Machine Learning. Both programs are not only taught by the best faculties of the institutes but also have industry experts to explain the industry application of everything learned. in AI/ML for Working Professionals.
For graduate engineers with a GATE score, IIT Guwahati’s new interdisciplinary MTech in Signal Processing and Machine Learning and MTech in Data Science is another path forward.
Career in Machine Learning – Your Path
If you’re still in school. The first step would be to take up subjects like Mathematics and Computer Science. You can start to learn to code using sites such as DataCamp, Codeacademy, or HackerRank. To understand the fundamentals of computer programming once again you have several NPTEL courses on Introduction to Python, or MIT OCW’s Introduction to Computer Science. For your undergraduate, you must preferably choose a STEM or allied field such as Engineering, the Basic Sciences, Computer Science, Statistics, or Mathematics. And begin taking online courses.
If you’re not from a STEM background, you have to build your mathematics on subjects such as Linear Algebra, Vector Calculus, Multivariable Calculus etc. Several such courses can be found on the NPTEL website or on MIT OCW.
To begin with your course on Machine Learning, for a complete thorough background- Coursera founder Andrew Ng’s course on Machine Learning and a subsequent post on Deep Learning and Neural Networks is the perfect starting point. Overwhelmed by the underlying theory? You could always opt for the lighter practical oriented courses such as University of Michigan Applied Machine Learning in Python. Udemy has a complete repository of courses aimed at different levels taught by various industry experts.
If you wish for a career switch or somehow find your background in the non-STEM field is weighing down, you could always go for the professional certificate courses offered by Great Lakes Learning, Imarticus Learning, and UpGrad. Great Lakes offers a Post Graduate Program in Machine Learning, a 7-month long program which can be taken either as an online course or as a regular weekend class. Imarticus Learning offers a PGP in Analytics & Artificial Intelligence and a pro-degree in ML in association with IBM. Again this course can be taken as a regular classroom course or by the online mode. UpGrad offers a Masters Program in Machine Learning & AI in association with IIIT-Bangalore.
To Sum Up…
Machine Learning is the perfect career for you if you enjoy numbers, computers and apply your knowledge to make real-life choices and decisions.
These are some useful courses if you wish to pursue a career in machine learning:
https://www.upgrad.com/masters-in-ml-ai-ljmu-iiitb/
https://imarticus.org/machine-learning-prodegree/
https://www.greatlakes.edu.in/e-learning/post-graduate-program-in-machine-learning
https://timestsw.com/course/iimk-artificial-intelligence-machine-learning/
https://www.coursera.org/learn/machine-learning
https://www.coursera.org/specializations/deep-learning
https://www.datacamp.com/tracks/machine-learning-fundamentals-with-python
We hope this is going to be helpful if you are planning to pursue a career in machine learning. For more guidance, feel free to connect with us and provide your feedback as well, so that we can also improve in the future.
