How to become a Data Scientist or Machine Learning engineer?

Do you want to become a Data Scientist?

Join machine learning & data science course to become a data scientist. Online video course to help you with;

  • Building your portfolio & profile
  • Machine learning fundamentals
  • R programming language & Python
  • Applied Statistics
  • Supervised machine learning models like linear regression, logistic regression, neural networks etc.
  • Unsupervised machine learning models like PCA, clustering etc.

How to become a data scientist or machine learning engineer? If you too have been thinking about it, you are not alone. A lot of students and working professionals have been trying to get into high paying and high growth filed of machine learning and data science.

I constantly receive this question and a lot of time, professionals with lots of experience talk about enrolling in machine learning and data science courses because they want to switch to this field.

So, in this post I will try to answer, “how to become a data scientist” and break it down for you.

We will cover following topics about “how to become a data scientist” in this post;

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  • Overview of machine learning and data scientist job profiles
  • Ideal candidates for machine learning and data scientist roles
  • Skills required for making into data science and machine learning
  • Is it for you?

Overview of Machine learning & Data scientists job profiles

There are variety of options for machine learning careers.

Overview of Machine learning & Data scientists job profiles

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But the problem is, field is new and there are lots of job openings with different names therefore it becomes very difficult to find out an appropriate job profile for yourself.

For example- a lot of time machine learning engineer and data scientist’s job description is same, but you may not apply for machine learning engineer if you have been only looking at data scientists job openings.

Similarly, there are lots of job openings for big data engineer/professionals focusing on skills like big data, spark, pig, hive etc.

These job openings are more towards the technical and infrastructure side of machine learning so you may end up applying for them even if you have only prepared for data scientist roles.

Preparing for big data engineer will include focusing on learning data warehousing and frameworks like pig, hive etc.

But if you are preparing for data scientists’ roles, you should be preparing for R programming, R libraries like dplyr, ggplot2, python for machine learning, sci-kit learn library, tensorflow, keras etc.

Big data engineer and machine learning engineer/data scientist roles could be very different from each other.

Good data scientist is going to be an advance version of business analyst who are not only good at programming side of it (R programming or python) but also well verse in requirement gathering, stakeholder management, requirement prioritization and other typical business analysis activities.

Data scientist is a hybrid role including four major areas;

  • Programming with R or python
  • Applied statistics with good understanding of basic concepts like confidence interval, mean, median etc.
  • Data visualization using a programming language or some tool like tableau.
  • Machine learning models like logistic regression, CART, ANOVA, random forest, neural networks etc.

There are also niche data scientists who are not dealing with R or Python, but they work with excel, c++, java, SPSS or SAS.

But in terms of other requirements, they too need to be hands-on with statistical concepts, machine learning models and data visualization.

Thus, when you are preparing for data scientist roles, you should spend some time doing research about the type of job profiles you are going to target. And based on that, you can prepare accordingly.

You can use any major job portal for your research like linkedinglassdoor indeed or Naukri.

Some of the common designation which you can run on these major job portals are;

  • 1
    Business analyst
  • 2
    Business analytics
  • 3
    Data scientists
  • 4
    Machine learning engineers

Go through their job description and see what kind of skills are required to make it for the role of data scientist. And start from there.

Always keep the end in mind while preparing for machine learning profiles.

Ideal candidates for Machine learning & Data Scientist roles

First you need to understand where you are today and where do you want to be in next few years.

If you are an engineering, commerce, finance or statistics students, this is probability the best opportunity for you guys.

If you are currently working as business analyst, data analyst, system analyst, IT programmer or project managers, you can also jump on it to secure your career for another 10-15 years.

If you are not a student or doesn’t have IT exposure, it doesn’t mean that you can’t get into it. It’s just that you will need to position yourself differently because IT professionals have exposure to software development and that experience is an asset to software companies but if you are coming from some other domain, you need to see if you have something which can be sold as an asset to employers.

Your domain experience is very important and if you have descent experience of few years in any major domain like healthcare, retail, bank, insurance and few other major domains, you can sell yourself as domain expert.

So, there is nothing like you can’t join, it’s just that you will have to prepare well for technical and software side of it and position yourself as a domain guy instead of a technical person.

But if you are a senior professional like program or portfolio manager, I don’t think you should be getting into it.  

You should focus on management programs engineered for senior management professionals which teach high level overview of emerging technologies like machine learning and how to handle these projects.

Skills for Data Scientist & Machine learning roles

Some of the major skills required for becoming a data scientist or machine learning engineers include but not limited to;

  • Visualization for machine learning using programming languages like R or Python.
  • Applied statistics for machine learning focusing on mean, median, confidence interval, inferential analysis etc.
  • Machine learning fundamentals
  • Hands on knowledge and experience on popular machine learning models including but not limited to;
  • 1
  • 2
    Linear regression
  • 3
    Logistic Regression
  • 4
    Dimension Reduction Technique like principal component analysis
  • 5
    Tree-based machine learning techniques like CART and random forest
  • 6
    KNN or K-nearest neighbor
  • 7
    Naïve Bayes
  • 8
    Neural network machine learning technique
  • 9
    Data reduction techniques like clustering focusing on K-Means

These models are must if you are serious about getting into data science and machine learning industry. Off course, there are other fields also like deep learning, natural language processing but they are niche fields. Machine learning and data science are generic profiles with widest applications. So, it’s better to target them.

Also, it’s relatively quicker to learn them so you can start it early.

Learning programming and statistics can really get tricky because these are older fields and there is vast amount of content available for these subjects.

If you are not careful with what to learn and what not to learn, you will end up wasting lots of time just on these subjects.

Good thing with technological advancement is that you don’t need to master mathematics, statistics or programming to become a data scientist.

In current world, most programming languages like R and python are evolved enough to do everything for you, you just need to have an understanding on how to use these tools to perform data science.

You can’t afford to spend years learning these subjects if you don’t have any or have limited experience in them.

To make your life easy, you can enroll in data science and machine learning course because these courses are custom made for aspiring data scientists and they only cover applied part of statistics, programming and visualization which makes reduces the content without compromising the quality.

Again, make sure you don’t end up spending lac of rupees or thousands of dollars on these machine learning courses.

You should go for some course which is affordable while delivering enough content to you so that you can understand what you are dealing with.

I have seen lots of professionals going for expensive courses from big reputed universities, just to realize that data science and machine learning is not for them. Everything is not meant for everybody and if you don’t enjoy working with statistics, data and programming languages, you won’t find it interesting.

A lot of these courses comes with the long duration of 6-12 months. You also need to account for your time along with money you are going to invest in them.

Disclaimer- I have also got a course on machine learning and data science for aspiring data scientists. If you are interested in that, you can signup for discount coupon and get it only for INR 4000 or $65. 

So whatever course you select, make sure it’s not very expensive and cover all the topics mentioned above to give a beginning point.

After finishing your course, if you are sure that you love it, then you can go for some full-fledged course.

Is Data Science for You?

Is data science for you?

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As I have mentioned earlier, always start with a pilot project or trial run and then decide if is for you. Because only you can answer if you enjoy;

  • Statistics
  • Data visualization
  • Data management
  • Programming language

Data science and machine learning are really booming and if you can get your foot inside it, you can really make it big. These are going to dominate world for next 10-15 years and if you are good at above mentioned four points, it would be foolish to not get into it.

Especially if you are working or planning to work in information technology sector because job prospects are not very good for other profiles in IT sectors. Hike is going down and growth is limited.

Therefore, if you are going to work in software industry, it’s better to work in the best domain of it.

So, what do you think? Do you still have any doubts?

Why you don’t you leave your comments and share your opinion.

About akhilendra

Hi, I’m Akhilendra and I write about Product management, Business Analysis, Data Science, IT & Web. Join me on Twitter, Facebook & Linkedin


  1. Your information is exceptionally intriguing. Much thanks to you for sharing. In any case keep up the astounding quality composition.

  2. It requires knowledge of Statistics, some Mathematics (Linear Algebra, Multivariable Calculus, Vector Algebra, and of course Discrete Mathematics), Operations Research (Linear and Non-Linear Optimization and some more topics including Markov Processes), Python, R, Tableau, and basic analytical and logical programming skills.

  3. Mubashira says

    Hi sir
    I have completed my BE graduate in computer science stream in the year 2017and I was very much interested in data science and machine learning . In search of that I got cheated by one or more institute and lost lots of money . If I take up this course as a fresher will I get job ?

    • Hi Mubashira, i know there are lots of institute which promises lots of things but can’t deliver. In this course, you will learn all major machine learning models with R and Python. This course will also teach you how to prepare your profile on major job portals and create your portfolio on github. If you follow everything in this course, your chances of getting job in machine learning will significantly improve but it all depends upon your effort because you have to crack interviews. if you just complete the course with minimal efforts or fail to answer questions in interviews, you won’t get job. So i won’t promise that by just completing this course, you will get job but i am sure if you put efforts and learn everything taught in this course, you will be better positioned to get into machine learning. And yes, it is only INR 4800 right now so this course is much more affordable than most other machine learning courses available in the market. Please let me know if you have any other question.

  4. Sir,
    I am a Mechanical Engineer and currently working in thermal power plant (pse) for last 7 years, having total 9 years of experience, 2 years as project planning and progress engineer. I am not satisfied with my current job, chance of improvement in career and standard of living is very slow. I love mathematics and passionate for learning analytical subject like data science. I don’t know whether this course is ideal for me or I shall struggle in finding jobs in this field as I’m already 32 and don’t have prior experience in programming.

    If this field is not suitable for me, kindly suggest some analytical and operation research based course or certification which may add value to my career.

    • Thanks Sourav for reaching out to me. As far as your age is concerned, there are much older people who are moving into machine learning because field is new so most of us who have learnt it, have done it after their college. If you want to bring material change to your life, you have few options at this stage;
      1. Executive MBA
      2. Machine learning
      3. Relevant certifications

      Nothing can beat regular MBA so executive MBAs are good but not that good. But if you don’t want to get into programming, that could be your best bet. You can look at 1 year MBAs offered by premier colleges like IIMs etc.

      Now coming to machine learning & data science, i won’t say that this is not suitable profile because you have got engineering background and had earlier exposure to math/statistics. Practically, there are many professionals who have switched to data science and machine learning fields with no prior experience of programming so that’s not the problem but it will be challenging. So you need to decide how comfortable you are with it. Because this course is comprehensive and covers all the major machine learning algorithms but this is just the beginning, you will have to practice a lot and create a good portfolio. But if you can dedicate next few months to it, i don’t see any reason why you can’t succeed especially if you like math and analytics.

      If you can’t go for Executive MBAs due to time or money constraints and are not comfortable with machine learning, you can also look at relevant certifications. When i say relevant, i mean certifications which are closer to your current job profile like project management or business analysis certifications.

      Please let me know if you have any more questions.

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