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So You Think You Can Be A Data Scientist? – Tanmoy Ray

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So, you think you can be a data scientist. But, are you sure you have it what it takes to excel in the data science field? It's a very complicated field, and getting competitive day by day. In this post, we will go through what the industry demands of a modern data scientist in the real world, how to become a data scientist, top platforms and resources to learn the data science skills, and career advice & job search tips from data science experts. The data scientist job is definitely one of the most lucrative and hyped job roles out there. More and more businesses are becoming data-driven, the world is increasingly becoming more connected and looks like every business will need a data science practice. So, the demand for data scientists is huge. Even better, everyone acknowledges the shortfall of talent in the industry. But, becoming a data scientist is extremely complicated and competitive. The career path of a data scientist is not going to be easy.


12 Mistakes that Data Scientists Make and How to Avoid Them

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It needs a mix of problem solving, structured thinking, coding and various technical skills among others to be truly successful. If you are from a non-technical and non-mathematical background, there's a good chance a lot of your learning happens through books and video courses. Most of these resources don't teach you what the industry is looking for in a data scientist. In this article I have discussed some of the top mistakes amateur data scientists make ( I have made some of them myself too). And we will also look at steps you should take to avoid those pitfalls in your journey. Many beginners fall into the trap of spending too much time on theory, whether it be math related (linear algebra, statistics, etc.) or machine learning related (algorithms, derivations, etc.).


13 Common Mistakes Amateur Data Scientists Make and How to Avoid Them?

#artificialintelligence

So you've decided data science is the field for you. More and more businesses are becoming data driven, the world is increasingly becoming more connected and looks like every business will need a data science practice. So, the demand for data scientists is huge. Even better, everyone acknowledges the shortfall of talent in the industry. However, becoming a data scientist does not come easy. It needs a mix of problem solving, structured thinking, coding and various technical skills among others to be truly successful. If you are from a non-technical and non-mathematical background, there's a good chance a lot of your learning happens through books and video courses. Most of these resources don't teach you what the industry is looking for in a data scientist.


Here is What I've Learned in 2 Years as a Data Scientist - KDnuggets

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It has been 2 years ever since I started my data science journey. Boy, that was one heck of a roller coaster ride! There were many highs and lows, and of course, countless cups of coffee and sleepless nights. I failed a lot, learned a lot, and of course, grew a lot as a data scientist along the journey. Throughout my journey in these 2 years, from writing on Medium, speaking at meetups and workshops, sharing my experience on LinkedIn, consulting clients on data science projects, to the current stage of teaching data science in education, I find joy and fulfilment in sharing and teaching to help others in data science and make an impact.


The Ultimate Guide to Land your First Data Science Internship

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I came across all kinds of advice when I was looking for a data science internship. But surprisingly, not many people talk about how to land that internship. My learning journey during my internship with Analytics Vidhya was equal parts challenging and fulfilling. I realized how vast and complex data science is and how unprepared I was for a full-time role. My path to become a data scientist would have been far more arduous and difficult one if I hadn't first interned. Even for experience people – internships are a very effective way to break into data science. We have now seen so many successful transitions enabled by internships. If you are looking for tips to prepare yourself for a data science internship, then you've come to the right place! In this article, I've drawn on my experience on the key aspects you need to know to land your first internship in data science. Each section is filled with plenty of tips, tricks, and resources. It won't be easy – but you would know what needs to be done. If you are looking for a guided journey with mentorship – check out our Certified Program: Data Science for Beginners (with Interviews) .