Machine Learning field - How to build a strong career

9th Dec 2019
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Machine Learning Field - How to Build a Strong Career


Machine Learning made its way in almost all places. Smartphone apps making our life smarter, Marketing campaigns working like charm, or the virtual personal assistant playing your favorite song and what not?


Machine Learning Field

Machine Learning Field

Machine Learning, a popular application of Artificial Intelligence, is exploding each minute and proving its potential with its smart algorithms. As Machine Learning applications continue to invade different verticals, so is its demand for “highly skilled Machine Learning professionals”. Though Machine Learning has invaded your driving seat, one cannot neglect the fact that it has created many new job profiles in the employment sector. We were now offered with trendiest jobs that pay well and feeds our creativity. Before analyzing on how to build a strong foundation in Machine Learning career, let’s see what Machine Learning is.


What is Machine Learning?


Machine Learning is training the systems to learn from examples and experience. Programmers are no longer going to write tedious codes to make machines work instead they are just feeding enough data and algorithms allowing machines to build their logic.


Machine Learning is a subset of Artificial Intelligence which allows computers or systems to make their predictions and data-driven decisions based on their experience. Without human intervention, the algorithms that are fed to the computer is making machines to learn on their own and improve over time. Well, we can now boldly say, Machines are turning smarter and we are making them do so.


Why Machine Learning jobs are constantly in the spotlight?


Artificial Intelligence and Machine Learning have the potential to boost the profitability of a business by automizing many tasks. Due to this very reason, many organizations started jumping into the effort of implementing Machine Learning into their company’s operations and it is predicted that this implementation will only continue accelerating in the coming years.


When the Business market scenario is supporting a positive environment for the growth of Machine Learning, it has a direct effect on the job market too. Machine Learning Engineer role has claimed its number one position in job sites due to hefty paychecks and faster career growth.


What are the Machine Learning job roles available at the job market?


Machine Learning Engineer is the most important role that will be assigned when you are ready for the job. You will be responsible for designing and implementing algorithms using your programming knowledge and address the business challenges.


Apart from Machine Learning Engineer, there are many roles available and they are Machine Learning analyst, Machine Learning Scientist, Data Architect, Data Scientist, Data Mining Specialists, Cloud Architects, and Cyber Security Analysts, and more. After a few years of experience as a Machine Learning engineer and depending upon your interest, you can further establish your career in this field.


What are the needed key skills to get into a Machine Learning career?


Let’s start this process by investing a couple of weeks in browsing and gaining knowledge about the basics of Data Science, Artificial Intelligence and Machine Learning. Then, move on to the finer details of it. Once done, follow these steps to lay a strong foot in the Machine Learning career



  1. Start with statistics: If you are an expert in understanding the concepts of statistics, then revise the following topics Data structures, The basic principles of probability, variables and summaries, Inference for numerical and categorical data, Distributions of random variables, Sampling, and Linear, multiple and logistic regression. If you have just the high school knowledge of Statistics and have not touched the books since then, still you can do a fresh start and understand the theory behind these concepts.
  2. Get a language knowledge: Be it R or Python, programming is not like olden days which could claim your eternal quest to become familiar with it. Both R and Python are quite popular and easy to learn as well.
  3. Understand supervised and unsupervised Learning models: Learn these models and try practicing on a different set of Data.
  4. Gain knowledge about Big data and analytics: Data is everywhere and it is your turn to juggle with it. Try to get a firm grasp on Big data concepts and analytics to work on them efficiently.
  5. Try hands-on real-time project: A Data project completed with all your knowledge will help you to kick start the Machine learning career in a better way.


How to build a Rewarding Machine Learning career?


Machine Learning career is the hottest career choice that comes with a fat paycheck. Besides, there is a huge demand for trained Machine Learning professionals and it is predicted to grow vertically in the coming years. While Machine Learning jobs are offering a good amount of salary for aspiring professionals, it is also essential for professionals to keep some key things in mind.


  1. Unlike other professions, the Machine Learning field is constantly evolving. So, it is not a one-time study after getting certified and being industry-ready instead one needs to constantly update their knowledge on upcoming changes, news updates, and latest tools.
  2. Learning and increasing the knowledge by reading books, newsletters or even taking up an advance course regularly will benefit the most.
  3. Enrolling in online communities, groups, forums would help them to update your knowledge on new updates in the field.
  4. Last but not least, keep practicing the skills that you have learned by participating in quizzes and competitions.


Well, the future of tech is already here!!! So, don’t forget your career mantra, equip yourself with strong knowledge on this latest evolving technology ‘Machine Learning’ and stay ahead of the tide.


If you have any further queries on ‘How build career in ML’ reach me at DataMites. I am working as ML expert and guiding many professionals about how to get into ML field.

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