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The No-Code Approach To Data Science And AI
No matter your level of expertise and experience in this field, it is essential to have a good knowledge of using a no-code approach to working with data if your aim is to get work done fast and to have fun along the way.
Jul 13 ·4min read
In our age of intelligence, no-code approaches to doing certain things have sprout up and become so popular and essential to know. Using a no-code approach to doing something doesn’t necessarily imply that you do not know how to code. As a matter of fact, you need to be very comfortable with coding to be able to use a no-code approach well. Data science and AI is a quite complex field to apply a no-code approach but a few companies and start-ups have been able to utilize the full power of Artificial Intelligence to push the boundaries of technology so far that the tedious work of cleaning data and making predictions from data can be automated and done without having to write a single line of code. Obviously AI is one of the leading companies that has been able to perfectly create a no-code platform for Data Scientists and AI engineers.
Why Use A No-Code Approach?
You might be wondering why I am suggesting you learn to use a no-code approach as a Data Scientist or AI engineer. In this story, I am going to discuss the many benefits that come with using a no-code approach as a Data Scientist or AI engineer. It should be noted however that a no-code approach is not meant to replace the traditional method of writing code to get work done, but rather to compliment and improve the work you do as a Data Scientist or AI engineer.
It Is Super Fast
Using a no-code approach such as Obviously AI gives you the flexiblity to wrangle and process data about 5 times faster than you naturally would, using the traditional method of writing code. With a no-code approach, you can save so much time from the data cleaning and wrangling process which you can fix somewhere else for maximum productivity. Obviously AI in particular gives you the liberty to make predictions from data too, awesome right! Having a good knowledge of the concepts involved in what you are working on is a plus and will help you in understanding the outcome of the predictions you make with no-code tools like Obviously AI.
It Is Fun And Engaging
Using a no-code approach is very interesting and Obviously AI to be specific, has a very engaging UI that gives you the feel of being involved at every stage. You can literally see engaging visualizations as you clean your data or make predictions from your data. Compared to the traditional method, the no-code approach keeps you engaged with work and helps you focus on the task at hand.
It Increases Productivity
Coupling a good knowledge and understanding of programming concepts and principles with a no-code approach increaces productivity with work since work can be done so fast and focus can be centered on a specific task at a time. You can work with large bits of data in seconds and automate some tasks while working around the data to save you so much time and stress. This is to say that no-code machine learning enables businesses to deeply focus on making decisions and taking actions, while seamlessly doing AI without building large system infrastructure.
About Obviously AI
Obviously AI has simplified the traditional machine learning process into 3 steps. Now you can upload your data, click a couple of buttons, and perform data predictions in minutes — without code. This allows anyone to use machine learning and makes it effortless for everyone, regardless of your technical background. Forecast revenue, optimize supply chain, personalize marketing, build personas. You can now know what happens next. Learn more here .
Thank you for making time to read this story. I hope you learnt something and it has been helpful. You are welcome to share your thoughts and opinions in the response section and you can contact me directly on Twitter or LinkedIn . Also, the team at Obviously AI is ever ready to answer all your questions or inquiries. You can reach out to them on Twitter or on their website . Happy Hacking!
A big thank you to Anna Ayiku for proofreading and correcting the many mistakes I made writing this.
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