Kick Start Your Career in Data Science without Coding Knowledge

Though many coding geeks indeed choose to pursue a career in data science, learning data science is not just reserved for only those with coding knowledge. But the question often arises, does data science require coding? Many great enterprise data scientists began their careers in data science without any prior coding knowledge or experience. With this article, you will understand how you can start or switch to a career in data science even without any coding knowledge. Let’s begin…

 

To learn more about data science, read our blog – What is data science?

Learn How to Take A Step Forward

First, there are core data science skills. You need to be able to manipulate files of different formats, clean and explore data, use program algorithms to modify the data, and create data visualizations, etc.

Second, there is knowledge of mathematics and statistics. It is not necessary to have a doctorate in mathematics or statistics to have a successful career in data science. However, it is mandatory to have a sound knowledge of the essentials of statistics and Math. You should also know how to interpret the algorithms.

Must Read – What is a Data Scientist?

The last, but not the least, is business skills. Usually, people don’t pay much attention to improving their soft skills and business knowledge. The ability to identify which issues need special attention, how to work with interdepartmental teams, and communicating the results to the stakeholders to help make them crucial business decisions, is indispensable.

Pick Up an Online Course

As a beginner, it might be a little overwhelming to see your peers doing better with data than you. You would need to learn data science and related concepts from scratch. You have a sound knowledge and work on data, be consistent and diligent, and probably you will outperform everyone once you acquire the subject-specific knowledge.

Learn Data Science Basics

You can get enrolled in any online data science course as per your aspirations and professional requirements. Both paid and free courses are available to help you build upon your data science skills. You can consider taking up a full-fledged and paid data science course, take up a free course, or audit a course without getting a certificate. You must know that demonstrating the right skills to your hiring managers is extremely important.

Pick courses that give you a concrete understanding of the main aspects of data science, including programming in R, basic data cleaning, analysis, regression, artificial intelligence, and machine learning.

One highly recommended course is Executive Data Science Specialization. You don’t need any prior data science experience to take up this course, and you will learn the concepts of data science and implement them in the real world.

Some other courses that don’t require a prior coding experience to master data science, include –

• Data Science: Machine Learning by Harvard
• Introduction to Data Science with Google Analytics: Bridging Business and Technical Experts on Coursera
• Data Science Methodology on Coursera
• Data Science for Business Innovation on Coursera
• Machine Learning for Data Science and Analytics on edX
• AI For Everyone by IBM on Coursera
• Data Analysis with Python on Coursera
• Learning Analytics Tools by NPTEL

Learn Statistics

To succeed in your career in data science, you will have to work on different statistical tools and methods for data analysis/sorting/visualization. It is vital to have a good command and understanding of topics like statistical tests, distributions, maximum likelihood estimators, etc.

I would highly recommend you to pick specific statistics skills to make your resume strong enough to catch the attention of the recruiters. Some statistics courses which you must consider if you wish to enter the world of data science –

• Advanced Statistics for Data Science Specialization
• Data Science: Inference and Modeling
• Post Graduate Diploma in Applied Statistics
• Statistics for Data Science with Python
• Principles, Statistical and Computational Tools for Reproducible Data Science
• MicroMasters® Program in Statistics and Data Science
• Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions
• Data Science: Linear Regression
• Data Science: Probability

Learn Python

A Kaggle study reveals that Python, SQL, and R are the most popular programming languages. The most widely accepted, by far, was Python (83% of those surveyed used it). You need to get comfortable working with Python, as it comprises programmed functions, tools, and algorithms that can help you save a lot of time. It is a good idea to learn about Python libraries like PyTorch, Matplotlib, NumPy, TensorFlow, Keras, Pandas, Scikit-Learn, etc., and the ecosystem of data science packages in Python. Here are some of the popular Python Courses –

• Statistics for Data Science with Python by Coursera
• Python for Genomic Data Science by Coursera
• Foundations of Data Science: K-Means Clustering in Python by Coursera
• Python for Data Science by edX
• Data Science: Computational Thinking with Python by edX
• Python for Data Science and AI by Coursera
• Python Certification Training for Data Science by Edureka

Learn How to Build Your Data Science Projects 

Employers prefer hiring candidates with applied knowledge and skills. One of the best ways to showcase your skills, while enriching your learning is to build a portfolio that demonstrates all of those data science skills effectively. You should also start contributing to open-source projects on platforms like GitHub. You can collaborate with others and learn from their feedback and expertise.

Create 5 – 6 data science projects, relevant to the job role you are interested in. This includes data cleaning projects, data storytelling projects, end-to-end projects, explanatory posts by picking a specific data science topic, optional portfolio pieces, data visualization projects, group projects, etc.

Must Read – Interesting Data Science Project Ideas for Aspiring Data Scientists

Here is how you can do it –

• Find a suitable topic
• Extract relevant data from the web and clean it
• Dig deeper to get insights and utilize those insights in your project
• Try to build features for your future consumers using external APIs
• Explore some of the top data science platforms to help you learn how to build great data science projects.

Improve Your Business Skills

Let’s take a look at how you can improve your business skills –

• Understand business objectives and data-based information needs
• Interpret and contextualize the data in the best way possible to extract valuable information
• Prepare a clear and compelling presentation and communicate the data effectively through the right data visualization tools such as tally charts, histograms, scatter plots, etc.
• Learn how to make evidence-based decisions and present them to management and stakeholders

Lastly, Learn to Program!

You need to acquire the right knowledge of data analytics tools, technologies, as well as programming languages if you wish to grow in the field of data science. You don’t need to be an expert at any programming language, but its knowledge is something that will set you apart from others in terms of value addition. Learn programming languages through these online courses –

• Using Databases with Python
• Programming for Everybody (Getting Started with Python)
• Computer Science & Programming Using Python
• Introduction to R for Data Science
• Apache Spark and Scala (Online Classroom-Flexi Pass)
• Apache Spark 2 with Scala – Hands On with Big Data!

• Spark, Scala, and Storm combo
• The Complete Java Certification Course
• Java Programming: Principles of Software Design
• Kotlin for Java Developers
• Java Programming: Solving Problems with Software
• The Complete SQL Bootcamp
• SQL – MySQL for Data Analytics and Business Intelligence
• The Ultimate MySQL Bootcamp: Go from SQL Beginner to Expert

Conclusion

Embarking on a career in data science without prior coding experience is not only possible but also achievable with dedication and the right approach. 

To kickstart your journey, enrolling in online data science courses that cater to beginners can provide you with the necessary knowledge and hands-on experience. These courses cover various topics, from programming and data cleaning to artificial intelligence and machine learning.

Moreover, building a solid portfolio by working on data science projects and contributing to open-source initiatives is essential. This not only demonstrates your practical skills but also showcases your commitment to continuous learning and improvement.

In the ever-evolving field of data science, perseverance, continuous learning, and a strategic approach are vital to achieving success, even for those starting without coding experience. So, take that first step, embrace the learning curve, and open doors to exciting opportunities in data science.