Can I Learn Data Science Without Programming?

What is the Scope of a Data Scientist Without Programming Skills?

Don't worry if you don't have programming skills; no one can block your way to become a data scientist. Of course, having expert programming skills boost your career, but it's not essential as it is said to be.

It is said by many data industry experts that anyone who has basic programming skills or can easily understand the basics of programming such as functions, loops, and programming logic can become a data scientist.

We all know that data science is said to be the sexiest job of the 21st century. Besides, it is also called a highly lucrative job field. The prime reason behind the lack of data scientists is the demand and supply chain gap.

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There are many prospects for people to enter this profession due to the rising need for data scientists. However, a lot of people who don't know how to programme but have other abilities desire to work as data scientists.

A data scientist who is proficient in probability and statistics can hold this position. Additionally, data scientists must be proficient in modelling, business, communication, and other analytical abilities.

A proficient data scientist can examine the data and go into the details to discover important information. However, no one can stop you from becoming a data scientist if you have the ability to develop Python or R scripts or readily comprehend how SQL works.

Non-Programmers Data Scientist Can Acquire These Skills to Boost Their Career

Here is good news for non-programmer data scientists who want to enhance their skills. You can take some of these suggestions.

Be a master to use GUI based tools

You can pursue a career as a data scientist without having programming skills. Have you heard about GUI-based tools? They are GUI-driven tools used for data science projects such as Auto-Weka, Tableau, and Rattle.

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These tools exclude the programming aspect and facilitate a user-friendly interface. With the help of GUI-based tools, anyone who has a basic knowledge of algorithms can understand and develop high-quality machine learning models.

Most GUI tools are available free to use and help you to analyze and present data with the help of charts and graphs and other infographics. Thus, you don't need to have an excellent command of programming skills to use GUI-based tools.

Enhance your skills with business communication

Have you ever fantasised that your strong interpersonal abilities or prior employment in the insurance industry will help you further your career as a data scientist? No, not at all, but believe me. If you understand business acumen better than an excellent coder, you can be a good data scientist. Furthermore, you are definitely a valuable asset for any large organisation or business if you have expertise working in e-commerce, healthcare, or insurance. As a result, you may become a data scientist without knowing programming by honing your corporate communication abilities.

A Great Story Teller will be a good data scientist too

A data scientist's major responsibility is to dig insights, bring valued numbers, make models, and then present to stakeholders. If a scientist can't convey their work to stakeholders in a better way, they can't understand if and but's of data-driven decisions.

Having a great storytelling skill helps you pursue faster than a simple data scientist, so know your talent and groom it.

Recommendation to be a data scientist without programming skills:

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• IBM SPSS

  These days, IBM SPSS is particularly well-liked in the social sciences. It includes solutions and virtually complete coverage of statistical algorithms. A data scientist can import or export data into this programme. The SPSS user interface resembles a data table. The user may do statistical analyses such the T-test, ANOVA, or models after uploading the data.

  All common statistical tests and models, including logistic regression, the generalised linear model, and linear regression, are fully covered by it. Also supported by SPSS are machine learning techniques. What more is required.

• Azure ML Studio

  Here is another software that provides solutions for programming problems. The Azure ML offers solutions to machine learning platforms without needing any program. Its interface is similar to Rapid miner. Users can drag and drop components and can form a full pipeline. Besides, it also supports the R language. You can get full benefits of it while choosing Microsoft technology stack.

• IBM Watson

  If you want to work as a data scientist but lack the necessary coding abilities, IBM Watson may be able to help. The software provides a range of analytical skills. You may use sentiment analysis to determine an image's category. With its comprehensive toolkit, IBM Watson Studio, users can construct pipelines without needing to know how to programme.

  Data scientists with programming abilities can also utilise this because you can combine it with R studio and a Python Jupyter notebook to obtain further advantages.

• WEKA- Open source data mining and machine learning software

  Weka is another software for data mining and machine learning. Weka is written in Java and presented by the University of Waikato. It is also GUI based tool, but it has robust features as compare to other tools. It provides full coverage to machine learning models such as support vector machines, random forests, and ensemble methods.

  It can also help in data mining algorithms such as association rule mining. Weeks is famous for teaching data mining and machine learning to beginner-level students.

• Rapidminer

  Rapidminer was introduced in 2006 and is an open-source project. More than $30 million has been invested in it as of late. Now, using it calls for a licence. Users are made more convenient by RapidMiner's plug-and-play drag-and-drop interface. Any form of data may be loaded by a data scientist, who can then choose the processing to create various models. You may choose from a variety of models thanks to its extensive feature set without having to write a single line of code.

  It also provides script execution for Python and R. It provides simple features and potent capabilities to help data scientists who lack programming knowledge. Although the licence fee is hefty, the tool is useful.