Data Scientist without a certificate? Possible - DSBoost #3
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Data Scientist without a certificate? Possible - DSBoost #3
Welcome to the third issue of DSBoost, the weekly newsletter where you can discover interesting people in the ML/AI world, get the main takeaways of a relevant podcast, and stay up to date with the latest news in the field!
💬 Interview of the week
This week we interviewed Sumanth, who is a Developer Advocate. Enjoy:
What did you study?
I am not from Computer Science but I am passionate about Math and Statistics, so I thought let’s give Data Science a try. I eventually loved the field and stuck to it.
What are your favorite resources?
My go-to place to learn anything is Youtube.
I love the content of Made With ML
Deep Learning with Python by François Chollet
What got you into your current role (portfolio, certification, etc.)?
I don’t have a single certification. Everything that I am currently doing is possible thanks to Open Source and Building the Portfolio in Public.
What is the biggest mistake you've made?
When I started learning Data Science, I focused more on theoretical concepts and less on doing and building projects.
If you start now build more things!
What is your most significant achievement?
I was working in a Machine Learning Project that actually solves climatic issues and Accelerate Green Transition.
What do you enjoy the most in your work?
I love connecting with developers, helping them in their work and learning new things.
What tools do you use the most / favorite tools?
Pandas, NumPy, & Tensorflow - I use these every day.
I love Transformers from Hugging Face
Do you use ChatGPT or other Al tools during your work?
Who doesn’t use ChatGPT? It saves a lot of time when writing code, documentation or learning new things.
It doesn’t change my approach to problems but helps to solve those problems.
What is your favorite topic within the field?
I love each and every Machine Learning Concept but if I have to select one it has to be Transformers.
Which one of the recent AI/ML models will have the most significant impact on the industry in your opinion?
RLHF (Reinforcement Learning from Human Feedback), which is the base for ChatGPT, will have significant impact on various fields.
Can you share a fun fact about yourself?
I love playing Table Tennis and Cricket.
Travelling around the World before my 30s is on my Todo.
🎙️ Podcast of the week
Ken's Nearest Neighbors - Why are Data Science Jobs Disappearing? (Jay Feng) - KNN Ep. 135
Key takeaways:
Data science is a broad term that encompasses various skills and techniques, making it challenging to define a specific job role.
The definition of a data scientist has changed over time and may have contributed to a decrease in job postings for data scientists, focusing on more specialized roles within the field.
The demand for data scientists may also have decreased in recent years due to the shift towards automation and pre-built solutions and the saturation of the market.
The distinction between data engineers and data scientists is becoming increasingly important, with data engineers focusing on infrastructure and data management and data scientists on the analysis and modeling of data.
Data engineer roles have not been affected in the same way as data scientist roles because the data infrastructure they build is a critical component of any data-driven organization.
The demand for data scientists may increase in the future as the need for more advanced and specialized ML solutions grows. However, this is subject to change based on future developments in the field.
Despite this, the demand for data science skills remains high, particularly in industries where data is a critical asset.
Diversifying your sources of income, such as through content creation, is crucial for achieving financial stability and independence.
Developing additional skills and finding other ways to make money can provide fallback options in uncertain job markets.
🧵 Featured threads
This month we are recommending threads about resources, enjoy!
🤖 What happened this week?
Google is opening up its new conversational AI service, Bard, to select testers. Powered by the LaMDA language model, Bard draws on information from the web to provide fresh, high-quality responses and can be used to simplify complex topics, explain new discoveries, or learn new skills. Google is also working on AI-powered features for Search that will distill complex information and multiple perspectives into easy-to-digest formats and an API.
Microsoft announced an integrated search, browsing, and chat into a unified experience on Bing and Edge, with new features such as better search results, complete answers, interactive chat, and AI capabilities like content creation and financial report summaries. Users can get detailed answers and links to relevant content, as well as compose posts and summaries with the help of ChatGPT.
👥 Under the radar
Here are a few words from Sairam Sundaresan personally:
Hi, I'm a Research Scientist figuring out how to make computers understand the world like us. I've been working in computer vision and machine learning roles for the past 12 years building several products, publishing papers and patents. Outside of work, I like to share my knowledge and help other practitioners learn by making machine learning fun. I do this through videos on my YouTube channel and my weekly newsletter Gradient Ascent and, threads & doodles on Twitter. If that sounds like your kind of jam, come join the fun :)
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