Aspiring Data Scientists Get a Christmas Gift from Santa

The sky is grey, and the temperature is below -13 degrees. Somewhere in Lapland, Father Claus is sitting on a rocking chair, swirling, and sipping brandy beside the fireplace. Slowly, the big man gets up, with his massive belly pushing his overcoat buttons to the brink. Stroking his white beard, he wobbles towards the window. Out there, it is snowing, and Rudolph and his gang are nibbling on the ferns. Father Claus turns around with a gloomy look on his face (quite uncharacteristic of his peculiar disposition), perhaps, after watching a video feed of aspiring data professionals. As the new year approaches, aspiring graduates and interns in the data industry dream about kick starting their journey, but many are often overwhelmed by the fast-paced and ever-changing data industry.

Father Claus ponders for some time, and suddenly, there is a twinkle in his eyes, as if he got an idea or probably a new-found purpose. Father Claus's small smile grows wider as he becomes more focused on ensuring that the right gifts reach these kids. However, identifying what each child would want for Christmas this year will be more than a task. But Father Claus knows no obstacle is too great, and not all gifts have to be material.?

Now that he is getting old, father Claus wants to share and impart his eons of knowledge to all his children. He dusts up and boots his old computer and spends some time compiling a list of probable perfect gifts for the most special kids (all kids are special!) aspiring to be data scientists.

1. Develop an interest / passion

To learn and acquire knowledge in Data Science and Artificial Intelligence, one must have an interest and passion. Data Science is a complex yet fascinating field requiring both dedication and effort. And, if you are genuinely passionate about it, you will more likely find the solutions quite quickly.?

However, you will not achieve your desired results if you do not possess the necessary interest. If that does not work for you, there are many options available.?

2. Focus on fundamentals

A tremendous amount of mathematics goes into Data Science, particularly in Machine Learning and Deep Learning. Before you plunge deeper into Data Science, you must clarify the four fundamental concepts: Linear Algebra, Statistics, Probability, and Calculus. Head to Google, where you can find multiple resources for all these topics to learn and hone your concepts.?

3. Practice theoretical concepts

Reading, understanding, and remembering are all set and done. Certifications are important. But what if you can't use the algorithms, derivations, and theoretical concepts to solve applied issues?

The best way you can bridge the gap is by interning at a firm, practicing datasets, or taking part in competitions and challenges hosted on platforms such as Kaggle. When you begin applying the learned concepts in real-time, you'll be amazed at how much you can retain.

4. Master a programming language

Programming skills enable you to implement much of your mathematical knowledge as code. After all, coding skills are integral to Data Science projects. Trying to learn many languages quickly, in a short period, might make you a Jack of all trades but a master of none. So, if you choose to learn Python, stick to it till you master it, end to end. This time, the focus should be on getting the concepts clear and practicing continually.

5. Rely on research?

?Research plays a crucial role in Data Science. Whenever possible, use the internet to consult multiple references and resources before undertaking complex tasks. To be successful in Data Science, you must be aware of what you are doing. Hence, research and a thorough understanding of various concepts will enable you to produce thoughtful designs.?

6. Structure approach to solve a problem

You might have a case study or a puzzle before you. But the question is how you will solve it? What tools will you need for that? And many such questions. However, without knowing the answer to the questions, you won't build a framework. And, to create a framework, you must know how to structure your thought process to arrive at a solution. So, address the issue in the top to down order and make sure that your logic is sound.

7. Stay Updated

The Data Science technology or idea that is currently popular may not continue to be so next year or even in a few months. Machine learning is a simple example as architectures and models are constantly evolving. Keep reading various articles, research papers, and books to stay updated and stay on top of the learning curve. YouTube and blogs, too, are a great way to remain up-to-date.?

8. Communicate?

Data Science or any field for that matter today requires professionals to collaborate and work as a team to discuss or brainstorm. Today, companies seeking data scientists need someone who can concisely and clearly explain their technical findings to others in the business. Try to role-play a scenario where you explain a concept visually and verbally to a non-technical audience. This process will help you organize your thoughts and understand your standing in analyzing and your groundwork.

Staying true to the Christmas spirit, Father Claus feels satisfied that aspiring data scientists will be reading this and become wiser somewhere in the world. Father Claus springs to his feet, prints over a thousand copies of his pearls of wisdom, envelops them, dresses in red, loads up his sack, sprints towards Rudolph, and fastens him to the sleigh. And off they leave with a merry and hearty 'ho ho ho' to deliver the seasons' choicest festive gifts to data professionals.