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Self-Starter Tips That Will Make You A Better Data Scientist 
Self-Starter Tips That Will Make You A Better Data Scientist 

October 19, 2022

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Are you a self-starter in data science? If you are learning on your own, you need to read this article to keep yourself on track. We all know that getting started in data science is not easy. This is especially true for those working full-time and who are new to the field. To help you get started on your career in data science, I've come up with a list of some great tips that should point you in the right direction.

Is Data Science A Good Career?

Data Science remains one of the most rewarding and in-demand professions of the 21st century. Data science is the field that applies advanced analytical tools and concepts to extract valuable information for decision-making and strategic planning. With the rise in data volume, Data scientists are in high demand in almost every industry. They help in identifying trends and patterns in making better business decisions. 

 

With that being said, a data science career is satisfying and lucrative, but starting a data science career is not easy. However, the adventure is incredibly exciting, and with dedication, the right resources, and support, one can attain this position.

 

Let's move on to the tips and tricks that can get you started as a self-starter in data science.

Tips For A Self-Starter In Data Science

  1. Mindset – Be prepared to work Hard and Smart

Be curious and excited about learning new things. Since data science is a vast field, it can be difficult to determine what to focus on. Moreover, we are sometimes overwhelmed by the possibilities, which leads to confusion. Such overthinking may hinder our productivity and prevent us from moving forward. We are hesitant to pick one and move on because we are afraid of failing or making the wrong choices. Therefore, to move to a career in data science, you should start acting now! Keep your mindset tough by deciding that you will start now! Nothing is stopping you from trying out all your choices. 

 

  1. Pick up a programming language and be an expert in it.

Learn to code first before diving into the world of data science. Data scientists develop algorithms and the environments needed to execute such algorithms. Python and R are the most widely used programming languages for multiple reasons. Since they are both open-source and free, anyone can learn how to program in these languages. Moreover, the syntax and libraries of these programming languages are very user-friendly for beginners.

 

  1. Skillsets – Nail The Fundamentals

Keep in mind that working in data science or gaining data science skills does not require a degree. You can definitely become a data scientist with the right skills and a few projects in hand. Therefore, don't put yourself off thinking you don't have any relevant degree. 

Once you have mastered programming, start learning the basic concepts and aspects of data science. Below are the basic data science skills you need to get started as a beginner:

 

  • Basic and Advanced Technical skills:

With proper guidance, you can learn these statistical, mathematical, and advanced concepts behind data science and open up creative paths for manipulating and communicating data. 

 

  • Statistics
  • Linear Algebra
  • Calculus
  • Probability
  • Regression analysis 
  • Machine Learning
  • Neural Network
  • NLP
  • Deep learning



 

  • Data Science Tools:

As a data scientist, you must be proficient in various tools to process, analyze and visualize data. A few common data science tools include:

 

  • Jupyter Notebook
  • Github
  • TensorFlow
  • Tableau
  • SQL
  • Apache
  • SAS

 

Learning all these tools can be intimidating, but remember, you don't have to know everything. Instead of finding one perfect tool, start exploring with open-source alternatives until you find your favorite tools. 

 

  • Communication skills:

A career in data science requires not just technical skills but also soft skills. Communication, cooperation, and storytelling skills can set you apart from other candidates for data science jobs. Additionally, it will help you increase your sphere of influence inside your organization.

  1. Take up a Certification Course

Remember, having a relevant degree is not important in data science. A certification course or skills is all you need to get started. It's not that there aren't enough resources for learning data science; on the contrary, there are far too many out there. However, it might be confusing for you. This course will provide you with an in-depth understanding of basic and advanced data science concepts. With the assistance of mentors, you can improve your skills by working on various data science projects.

  1. Work On Multiple Data Science Projects

Start working on beginner-level projects once you have learned the data science fundamentals. You will find numerous project ideas available online. After all, you need to put your acquired knowledge into practice, and you can do so by working on industry projects. Practice what you study to make sure you understand along with the go. This will help you understand the concept and motivate you to learn more.

 

  1. Build an Impressive Portfolio

After working on a few data science projects, the next step is creating your portfolio. A portfolio can be a resume, CV, personal website, Github, and Kaggle accounts. Make an account on GitHub and Kaggle and participate in data science projects and competitions.

 

Since Recruiters first look at your resume before shortlisting, building an impressive resume is necessary. Make sure you include these pointers in your resume:

 

  • Write only relevant data science skills as per the job role you are applying for.
  • Mention all data science projects you have done to increase your chances. 
  • Bonus points if you include your Github or Kaggle profile. 
  • Always remember skills are more important than certificates. 
  • Most importantly, update your resume in an orderly format to look impressive and readable to employers.

 

  1. Consistency

Last but not least, your journey doesn't end here. Data science is an evolving field. Hence you need to keep learning and be updated with the latest data science tools. As with learning any skill, it is important to continually practice and learn as much as possible. Knowledge is power, so use this advice to broaden your mind to take your career to the next level!

Thus, you must maintain consistency throughout your learning journey.  

Final words!

It is a great time to become a data scientist due to the hot job market, competitive salaries, and endless rewarding career opportunities. 

Ultimately, a career in data science requires the right skill set rather than a degree. For a new data scientist, the road to success includes good knowledge of data science tools, having a rock-solid academic background in STEM, and most importantly, practice makes perfect. With steady hands and patience, you can easily strike out on your own - with these tips in mind.

 




 


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