How to Become a Data Scientist: A Comprehensive Guide

Data has become the new oil that drives organizational success in this digital age. Business strategies and decisions are now data-driven. This has given birth to the sharp increase in demand for data scientists as one of the most sought-after tech jobs in the industry. In this blog, I am going to be discussing the essential requirements, and skills as well as suggest useful links to valuable resources for one to become a skilled data scientist.

What Are The Requirements To Become A Data Scientist?

1 What Are The Requirements To Become A Data Scientist?
2 How Long Does It Take to Become A Data Scientist?
3 What Can I Do After 12th or Senior High School to Become a Data Scientist?
4 Is It Hard to Become a Data Scientist?
5 Is Data Scientist an IT Job?
6 What is a Data Scientist’s Salary?
7 Top 10 Recommended Courses and Online Resources
8 Conclusion
9 Frequently Asked Questions (FAQs) for Aspiring Data Scientists

Educational Background

There is a need for a strong educational foundation to be successful in every career.

Most aspirants have a degree in statistics, mathematics, engineering, or computer science. One can add to their resume a master’s degree but it may not always be necessary.

Technical Skills

Statistical Analysis: One needs to have a very good understanding of statistics and how to critically apply them in real-world scenarios.

Programming Languages: There is a need for proficiency in programming languages such as Python and R. These languages are mainly used for machine-building models and data analysis. Scientific Computing with Python is a free course offered by FreeCodeCamp to get you started.

Machine Learning: You can get a free course to enhance your skills with Simplilearn Machine Learning Algorithms which helps you familiarize yourself with algorithms and their implementation in different scenarios.

Data Analysis and Manipulation: A strong understanding of how to analyze, manipulate, or retrieve data using SQL is a foundational requirement. A free course Retrieve Data Using SQL.is offered by OpenClassrooms can be very helpful to you.

Soft Skills

Creativity and Curiosity: One needs to be naturally curious and creative to play around with data to achieve the desired results.

Communication: The ability to express clearly your findings to non-technical stakeholders is a valuable skill necessary to be a successful data scientist.

Problem-Solving: One needs to be able to approach problems that are complex methodically and come up with valuable solutions to those problems.

How Long Does It Take to Become A Data Scientist?

A step-by-step approach to become a Data Scientist

Just like any other career, it all depends upon dedication in your learning path to learn from the very word go. Mostly it can take anywhere from 6 months of intensive study to several years to become a skilled data scientist.

Fast Track (6 months to 1 year)

This can apply to both freshers and those with a strong background in the subject. It all takes full-time dedication, boot camps, engaging in hands-on projects, and taking online courses to reach your goal within a year.

Self-Paced Learning

Some who may be working professionals have other commitments, they may opt for this, and may take a bit longer typically 1-3 years. The time frames are determined by the level of dedication to your studies.

Traditional Path (2-4 years)

Aspirants can opt for a bachelor’s degree followed by a master’s degree in a related field which can be about 4 years. You can make use of the practical experience gained from internships gained during this period.

What Can I Do After 12th or Senior High School to Become a Data Scientist?

List of skills needed to be a professional Data Scientist

If you start your career earlier, it always gives you several advantages in the industry, and here are the steps you can take after completing your senior high school or 12^th grade.

Enroll in a Relevant Degree

You can take up a bachelor’s degree in statistics, computer science, engineering, or mathematics. During your program, you have to focus on courses such as programming, data analysis, and statistics.

Take Certifications and Online Courses

Platforms such as edX, Coursera, and Udacity can help you improve and supplement your skill set as they offer practical project-based courses and certifications.

Build Your Portfolio

You must participate in hackathons, take on personal projects, and contribute to open-source projects. Data Science is a practical career that needs hands-on experience that you will showcase to potential employers.

Take on Internships

You can gain industrial exposure and work experience by taking on data-related roles during internships.

Is It Hard to Become a Data Scientist?

Every task, course, or job you may decide to do looks challenging at first but when approached with the right mindset and resources it is achievable in the end. Data Science requires one to have analytical thinking skills, technical know-how, and be a continuous learner. You also need resource access, strong determination, and practical experience to bypass the challenges you will come across.

Is Data Scientist an IT Job?

Even though there is a very close relationship between IT and data science, the difference lies in its application and focus. Data Scientists collaboratively work with IT professionals, whose focus is on managing IT infrastructure, their primary focus is on the extraction of insights and making data-given decisions. Data science revolves around business, computer science, and statistics.

What is a Data Scientist’s Salary?

Due to the high demand for their technical skills and know-how, data science is a highly rewarding career option in this digital age. Their salaries vary based on industry, experience, and location.

For example, a data scientist working in the healthcare industry in Australia can earn less than one who works in FMCG in Asia. The following are examples of general salary ranges:

Entry Level

As a newbie in the industry, data scientists earn between $70,000 and $90,000 annually.

Mid-Level

After earning a few years of experience, the salary ranges from $90,000 to $120,000 per year.

Senior-Level

An experienced data scientist and those in managerial positions earn up from $130,000 to $200,000++ per year.

NB: For a piece of more detailed salary information and the latest figures, you can visit useful websites such as Payscale and Glassdoor.

Top 10 Recommended Courses and Online Resources

I have compiled a list of some of the many valuable courses and online platforms that will benefit you in your journey towards becoming a successful data scientist :

· 1. FreeCodeCamp Scientific Computing with Python

· 2. OpenClassrooms Retrieve Data Using SQL

· 3. Simplilearn Business Analytics with Excel Fundamentals

· 4. OpenClassrooms Create Dashboards with PowerBI

· 5. OpenClassrooms Create Dashboards with Tableau

· 6. CognitiveClass Data Analysis Courses

· 7. CognitiveClass Data Visualization with Python

·8. Kaggle Data Cleaning

9. Kaggle Introduction to Deep Learning

· 10. Simplilearn Machine Learning Algorithms

Making use of these useful platforms and resources will help you to acquire the necessary knowledge from beginner to expert in the field of data science.

Conclusion

In this digital industrial age, choosing data science as a career is truly a rewarding profession that requires analytical thinking, technical skills, and continuous learning. To become a successful data scientist, you can follow the outlined steps, making use of the valuable resources together with strong determination or commitment, you can start your career in this lucrative and exciting career. It doesn’t matter that you are just coming from senior high school or simply looking for a change of career, the road to becoming a successful data scientist is worth pursuing as it is within your reach.

Frequently Asked Questions (FAQs) for Aspiring Data Scientists

1. Do I Need a Degree to Become a Data Scientist?

Answer: It is an added advantage and beneficial (having a degree such as Statistics, Computer Science, or Mathematics) but not strictly necessary. There are alternative paths such as boot camps, online courses, and self-study that one can take on their journey to become a successful data scientist. The most important thing is to build a solid portfolio by doing projects and acquiring the necessary skills along the way which can be demonstrated to potential employers.

2. Can I Become a Data Scientist Without Knowing How to Code?

Answer: The key skills of a data scientist involve data analysis, manipulation, and building models. The common programming languages are R and Python. Even without any coding knowledge, with continuous practice, dedication, and making use of the various platforms, and resources such as FreeCodeCamp’s Scientific Computing with Python they will help you to learn and acquire the required coding skills.

3. What Tools and Software Do Data Scientists Use?

Answer: Data Scientists make use of a variety of software and tools to build models and analyze data. Amongst them are the popular:

Programming Languages: Python, R

Data Visualization: Power BI, Tableau, Matplotlib (Python library)

Data Analysis and Manipulation: Pandas (Python library), SQL

Big Data Tools: Apache Spark, Apache Hadoop

Machine Learning: Tensorflow, Scikit-learn(Python library), Keras

To get familiar with some of these tools, you can take courses such as Classrooms Create Dashboards with PowerBI and OpenClassrooms Create Dashboards with Tableau

4. How Do I Gain Practical Experience in Data Science?

Answer: To become a proficient data scientist, you need to gain practical experience by doing some of the following ways:

Taking part in Kaggle Competitions: It is a platform that offers people to participate in its data science competitions for a prize
Doing Online Courses: Most of these courses include hands-on projects and assignments to help you gain practical experience
Personal projects: You can use publicly available datasets to work on personal projects that are interesting to improve your skill set.
Open Source Contributions: You can contribute on platforms such as GitHub to your data science projects.

5. What Industries Hire Data Scientists?

Answer: There is a high demand for data across various industries because of the valuable insights they give to organizations in making informed decisions Industries that hire data scientists include:

Finance: Financial institutes and banks make use of data science for investment strategies, fraud detection, and risk management.
Telecommunications: They analyze customer data in the prediction of usage trends and service improvement.
Technology: Companies such as Amazon, Facebook, and Google heavily depend on data science for optimization and product development.
Retail: Industries in this sector use data science to predict customer behavior, inventory management, and sales forecasting.
Healthcare: They help improve patient outcomes, and personalized medicines through data-driven medical research.