Suppose you are giving an exam for a particular subject, take statistics as an example in your degree college, and you have 3 months.

 Can you study for this particular exam using online free content and think that you will score well in the exams? Did you understand the concept well? Will you be able to perform well in the exam? 

The same case is with Data Science. We cannot learn Data Science from online free materials without proper guidance and plan.

In this article, I have listed different ways to become an expert in data science.

First Option

To get a formal education in data science which may be in

education degree
  1. Engineering in Computer science 
  2. Master in computer science
  3.  Specialization in Analytics

So there are courses like the master’s in Analytics, which will help you get a structured education and will make you ready for the job market.



Second Option

  If you want to learn by yourself it will take you a long time. You will not be able to focus because data science is like an ocean, and you will get confused, and not have any accountability.

  You can still do it, but you need a lot of dedication, and 80% of the people are not able to succeed and do not get a good job 

Image: Illustration representing the process of standardization in statistics, with data points transformed into a common scale for meaningful analysis 
Becomes Frustrating and you Quit

  If you are lucky you may get interview calls, and due to high competition there are chances you are rejected and that is demotivating and frustrating and you lose your chance to work in that company.



 Third option 

 You can fast-track and hire a mentor who can tell you what is required to learn in a very structured and guided way so that you are ready in 6 months.

 I will suggest the best practice, you can spend two months figuring out online about data science on different topics in Python, SQL, statistics, etc.

But when you are serious about transition and preparing for an interview to a job you need some special attention to focus and sharpen your particular skills that are asked and tested in interviews and, for that you need some professional help this will help you in your career and it will reduce the hours you have pasted in frustration and rejections.

Benefits of Mentoring

In my 18 years of experience and taking hundred-plus interviews, people are not able to answer very basic questions and are not able to show that they will be able to deliver in a data science job. They think that by seeing some YouTube videos they can call them Data scientists, but this is just a myth.

This article is trying to convey the message that learning data science is just like learning a subject or a course at a University. It has to be given special attention and a special curriculum.

So why do people pay thousands of dollars to colleges, because of the structured curriculum that they have designed and the college and university have invested millions of dollars in building that curriculum with research so that help students develop their overall skills

I understand there are a lot of online free things, but free is not always the best. It may just give you knowledge, but the theory and application come from practice with special guidance.

How I work with my clients and mentees is I understand

  1. Their current status
  2. Their profile and strengths
  3. What is their dream job 
  4. What do they want and like to do?

Then we map the current state to their desired state, with a customizable curriculum. I make sure he/she can focus on this particular curriculum and make a good profile and be ready for the job market.

So, in summary, we need to have a very structured approach to learning data science, and you need an accountability partner to know that you have practiced well and you are ready for the next challenge.

You need to build the basics strong, and when I talk about basics it looks like a building. You need to get your foundation strong with the main four pillars that I teach

  1. SQL
  2. Statistics and maths
  3. Python
  4. Machine learning

When this foundation is built over that there may come different algorithms, different dashboards, and different deep learning and machine learning models, things will keep coming up in the building but the foundation has to be strong and the companies mainly test the Foundation. So when you are doing a lot of free courses, you will only focus on the floors you will build one or two floors, but the foundation is not there so how do you think the building will last.

 I request you to have a serious thought about how you are approaching learning data science, and I would recommend you to think about some degree program in a University for analytics and data science or if you already have some work experience and you have some of the basic Foundation knowledge get into a mentoring with experienced people who are offering this particular service because they have experience and they know what is being asked for and build a concrete plan with proper accountability and this would really help you access the data science.

This field is very huge and there are a lot of things coming up and it becomes very overwhelming. You need to just stay focused and pass the steps one by one.

About Community  Owner: Mohammad Arshad, A Globally recognized expert in AI

With over a decade of experience, Mohammad Arshad has successfully enabled businesses to monetize their data and AI products. His technical and strategic expertise has helped 5 of the largest companies in the world, 10 SMEs, and 3 startups build effective Data and AI Strategies.

He founded Decoding Data Science in 2020, a successful AI Strategy consulting practice, and expanded into education in 2022 with the launch of DDS Academy.

Accenture, HP, Dell, LinkedIn, MAF, and other leading companies have recognized Mohammad as a Data Science and Strategy expert since 2005.

Mohammad Arshad has been teaching technical and non-technical audiences since 2008, making him a seasoned mentor and coach in the industry. He has helped 600+ individuals get their Dream jobs.

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