Mismatch between Data Science Job Market and Online Courses | What Should Aspiring Data Scientists Do?
As organizations continue to make the most value from their growing data, the demand for data scientists and machine learning engineers is an all-time high. This has also led to the mushrooming of many online course providers. With so many “me too” courses providers around, the quality of training is not consistent. This leads to a mismatch in expectations of learners – primarily students and early-stage working professionals.
In this post, we will try to give you a clear picture of what’s required in order to get into the data science job market, how to proceed, and the alternatives. Additionally, we will also look at how online courses on Hadoop, AWS, DevOps, Python can help aspiring Data Scientists.
Data Science and Analytics Job Market in India
Data is everywhere and almost every business uses Data Science and Analytics in one way or other. According to the Salary Benchmark 2019 Report and India Skills Report 2019, data science along with machine learning and big data analytics will play a key role in creating jobs in India. Read more about the 2019 – 2020 Data Science Job Market in India.
According to Forbes and many other leading websites, a full-time Masters in Data Science will be a very important degree in the next 10 years. But, online courses and certifications that are focused on re-skilling and up-skilling are also important.
Mushrooming of Online Course Providers in Data Science Space
There are many e-learning and online courses providers out there in the market. These companies advertise heavily, get many reviews (some of which are digital marketers and not always real users) and they offer different permutations and combinations of basic courses on R, Python, SAS, Tableau, Excel-based curriculum.
These courses often start by some basic introduction of mathematics/statistics, followed by hands-on visualization moving onto aspects of prediction and artificial intelligence. A few courses also contain domain-specific analytics – like sales analytics, human resource analytics, marketing analytics, financial analytics, etc.
The mismatch of expectations or disconnect begins when all those learners taking these courses or studying data science would like to refer to themselves as data scientists. They think that they can apply for data scientist job openings and succeed. But, the course providers also need to be blamed.
For not-so-well-informed learners, advertisements on “become a data scientist in 12 weeks or 6 months” are misleading.
In a price-sensitive market like India, when the learners don’t end up with desired outcomes, the whole e-learning vertical faces the backlash. This also hurts the industry as the learners feel discouraged to up-skill and/or re-skill.
What should Aspiring Data Scientists Know?
In short, as a data scientist, you should have
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Experience with common data science toolkits, such as R, Python, Weka, NumPy, MatLab, etc
- Experience with data visualization tools, such as D3.js, GGplot, etc
- Proficiency in using query languages such as SQL, Hive, Pig
- Experience with NoSQL databases, such as MongoDB, Cassandra, HBase
- Excellent applied statistics skills, such as distributions, statistical testing, regression, etc.
As you can see, you can never learn or master everything from the above list in 3 – 6 months. It actually takes 5 – 10 years. The field is evolving at a fast pace. So, this list can also change in 1 – 2 years.
Data Scientist is Just a Tech Job Profile and NOT the Only Tech Job Profile
The industry is not all about data scientists and machine learning engineers. There are many other job positions as well. You can join the tech sector without becoming a data scientist. But, all the companies are focussing on the data scientist jobs only.
Learn to Become a Data Analytics Specialist or a Data Engineer
Secondly, most of the companies in India have got job openings in Data Engineering and Data Analytics and very few in the Data Science field, especially for freshers. Read more on Data Engineer vs Data Scientist – Backgrounds, Tools, Responsibilities, Job Roles, and Salaries and Data Science vs Machine Learning vs Data Analytics.
Where to Start?
- Learn the Data Science Fundamentals: Statistics, Data Exploration, and Basic Data Visualization
- Master a programming language; ideally, Python
- Learn the Pre-requisites of Machine Learning: Probability, Calculus, Linear Algebra, and other Machine Learning Basics
- Learn the advanced modules of Machine Learning and Time Series Modelling
- Know how to deal with Unstructured Data (including NLP)
- Get familiar with Deep Learning and Neural Networks
- Practice, Practice, and Practice
I would also like to mention that if you don’t know Python or R, better you learn SAS first. You don’t require prior knowledge in programming to learn SAS, and its easy-to-use GUI makes it the easiest to learn of all the three. More importantly, despite losing a little bit of popularity, SAS continues to have a say in hiring.
For more details on data scientist career path and how to get jobs, please read my previous articles – So, You Think You Can Become a Data Scientist and How to Get Data Science, Machine Learning, and AI Jobs.
What are the most in-demand skills among employers in 2019?
Here is the top-10 list:
- Big Data Hadoop
- Python Django
- Data Science with R & Python
- Machine Learning
- Artificial Intelligence
- RPA Tools
- AWS Certification
- Digital Marketing Analytics
So, rather than going for full-fledged courses on data science, you should consider taking one course at a time. Read more about the top 10 data science skills to succeed in 2019 as per data science experts.
What does the Employer Expect from Candidates?
You should be able to do some of the following tasks:
- Text Mining using Web Parsing of Data
- Social Network Analysis of a large data
- Ability to write complex SQL especially for Hive in Big Data
- Using NoSQL databases like MongoDB
- Using cloud for data science
- Using docker/Kubernetes/Terraform to make one-click deployment plus a deep understanding of the cloud environments (GCP, Azure or AWS)
- Understanding and/or curiosity for Deep Learning
It’s also recommended that you keep improving the skills in things that are not automatable:
- Communication skills
- Applied domain expertise
- Creating revenue and business value
What to do as a Fresh College Graduate?
Freshers have a lot of job openings. Most applicants would have done at least one course in the area, either online or in college. What will differentiate good applicants is their track record in usage. Good projects can make a huge difference.
Kaggle, Github and Hackathons are no longer optional – they show focus, dedication, and initiative besides improving coding skills.
A true data scientist is someone who also possesses domain expertise. Now, as a fresher, you are unlikely to have that. Hence, rather than going after “data scientist” job role, it’s better you focus on the jobs that can help you to practice what you have already covered and learned new things in order to get closer to become a data scientist in the coming years.
Best Online Courses on Data Science
In order to help the learners choosing the best online courses, we have aggregated the top online courses by various providers like Coursera, edX, Udemy, Edureka, Skillwise, Skillshare, etc. Here are our most popular articles on the curated list of online courses:
How does Edureka Differentiate from other Online Course Providers?
There are many leading online course providers out there. Edureka is one of the oldest. Secondly, we found many interesting reviews available on the Quora and other forums (sources mentioned at the end of the article). Rather than a bundle, courses are quite strategically created on a particular data science skill as per the job market. This also makes the courses a little economical for the learners. However, the courses are not the cheapest ones in the market.
Edureka is one of the oldest among all the leading online training and course providers in India. It provides live instructor-led online classes. However, they have got a few self-paced programs as well.
Edureka was formed in 2011 when Lovleen Bhatia (IIT BHU alumnus) and Kapil Tyagi (IIT Bombay alumnus) were trying to understand the needs of students and identify the difficulties faced by them as a part of the routine learning process at ABES Engineering College in Ghaziabad.
The larger vision was to start a venture that focuses on practical hands-on learning with industry experts mentoring and instructing students.
Earlier Days and Business Growth
Earlier, the courses were extremely popular in Delhi-NCR. Everyone knows how bad the traffic is in Delhi-NCR. The working professionals used to take up the online courses from Edureka while commuting from Delhi to NCR or the other way round.
The company did really well as they made Rs 30-crore company with a global footprint in the first two years. Currently, Edureka has a learner community of more than 700,000 professionals and students present across 100+ countries. The US contributes more than 40% of its learner base, followed by India.
Last year (in 2018), Leo Capital, a venture capital fund that invests in technology companies, invested USD $2 million in Edureka. It was their first round of VC funding.
Best-Selling Courses by Edureka for the Data Science Job Market in 2019
In order to know more about the Company, we reached to the Edureka Team. Here is the excerpt from the interview.
Q&A with Ankit Koushik from Team Edureka
1. With so many MOOC platforms and online course providers in the market, what does make Edureka unique?
Edureka is one of the pioneers in online, live, instructor-led training which gives us a unique positioning in the market. Other than this, we also provide lifetime access to course material and upgrades to the learner, 24×7 expert support and a unique learning approach.
2. Who are your learners?
Edureka caters to 80+ countries currently, most of these learners are working professionals between the ages 24 to 35.
3. Many people are in doubt if MOOCs are worth or not? Your thoughts?
Online learning is the future of education, as explained by several prominent educators. With the industry evolving at a rapid pace, online training makes learning and teaching more convenient for professionals. It also eliminates the cons of classroom training like transit times, finding good instructors etc.
4. Busy schedule and other responsibilities also take a toll. What would be your advice (or solution) for those learners who feel the need, but unable to take the shot?
We at Edureka are ridiculously committed to a professional’s learning and growth. Keeping that in mind, we provide each and every one of our learners with our unique set of features that lets them choose a schedule that fits for them. And, if they are unable to keep up, they can change this any number of times as they like. We believe that learning should not be a chore, rather it should be as easy as possible.
5. One of the major problems of the MOOCs and online courses is a huge drop-out rate? How is it with Edureka learners.
Edureka is one of the few online learning portals that boasts a decent completion rate. We see more than 80% course completion rate for our top courses. Each learner is assigned a personal learning manager who takes care of all issues and helps our users complete courses in the best possible way.
6. In today’s age, it should be blended learning. Undergraduate degrees in India should include online modules (maybe after partnering with providers like you). Has Edureka got such plans?
Yes, we have already partnered up with NITW for a postgraduate program in AI and ML. More plans are on the drawing board.
7. According to you, how should learners decide if they need one or two online courses or a full-fledged campus-based MS degree?
Most of the time, up-skilling and re-skilling come at a crossroad. But we believe, as does the industry show, learning should be continuous and professionals need to skill up multiple times to keep their careers secure.
8. With so many online course-providers and each of them offering multiple courses, learners feel confused and overwhelmed. Your advice – how should learners decide which one to opt for?
The basic criterion should be the quality of instructors, the kind of support the portal offers, the curricula covered, and finally the add-ons the user can expect.
9. How is the recognition of Edureka courses among Indian employers?
The Indian IT professionals group has embraced Edureka with open arms. This is not just evident by the number of people who buy our courses, but also who follow us on our other channels like YouTube, LinkedIn, and others.
10. Many course providers are offering their programs along with 1:1 mentorship. Does Edureka provide any kind of career and job support?
We do provide pre-placement support and try and connect our learners with any relevant openings whenever they are available with our corporate partners.
Featured Image Credit: Analytics India Magazine
Author: Tanmoy Ray
I am a Career Adviser & MS Admission Consultant. Additionally, I also manage online marketing at Stoodnt. I did my Masters from the UK (Aston University) and have worked at the University of Oxford (UK), Utrecht University (Netherlands), University of New South Wales (Australia) and MeetUniversity (India).
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