Mısra Turp

Become relevant with Data Science!

To be ready for tomorrow's world from today, what we need is clear: data skills.

Let's get started!

This might sound familiar

you feel like your current skills are not as useful anymore

you want tobe a prominent part of today's world

you're looking for ways toupgrade yourself and become relevant

but you don't have time for ineffective learning methods

you need a way to guide your efforts and stay in focus

you want to know that you are doing the right things

Hi there! I am Mısra,

I am a data scientist and I want to help you have a smooth transition into data science.

Before getting into data science I was working with robots and other branches of artificial intelligence for the fun of it. When I decided to become a data scientist professionally, I came across many barriers that lay between a motivated person and a data science career. Some of which being misinformation, infinite number of courses and a lack of clear information about fundamental data science knowledge.

On this website, my goal is to guide you on your journey so that you can make smart decisions about what to learn and how to learn it. This way, you can acquire the relevant skills without getting distracted by any buzzwords and keep your focus throughout.
I will be your guide by sharing my knowledge through articles and YouTube videos, interviewing data professionals on my podcast and preparing hands-on courses to help you pave your own path.


Deep Learning 101 with Python and Keras

Deep Learning 101 will teach you all the essentials of deep learning without wasting your time.

By the end of this course, you will be a confident deep learning practitioner, who knows how to set up a deep neural network from scratch, how to train it and how to improve its performance.

Learn More

Data Science Kick-starter mini-course (free)

This course is prepared to act as a guide to aspiring data scientists during the first steps of their journey.

The goal of the course is to help you identify clear goals and stay focused when learning data science. There are three modules in the course:

  • Determining your goal
  • Understanding the discipline
  • Understanding the learning requirements
Learn More
Emin Altun
“You have been more helpful than most of my teachers at school with what you have taught me in the last 1-2 months. Thanks to your YouTube channel I got a job offer where I do my internship.”

Take the Data Science Kick-starter course for free

  • Clarify your data career goal
  • Understand what to work towards
  • Learn about the necessary skills
And receive resources on becoming a data scientist sent right to your inbox
Enroll in the course now!

What students say about the course

“Straight to the point and short but very meaningful. It definitely guides me in a better direction.”

— Jorge Quiroz

“It gave me an insight of what a data scientist is. You have inspired me with the data science knowledge...thanks a lot!”

— Thomas Waas

“The whole course covers the proper guideline for a data scientist. Each and everything was important to me.”

— Zubair

“Organized info about getting into data science in a way I have not seen before!”

— Joshua Maxwell

Most popular articles

Deep Learning Fundamentals: hyperparameter tuning techniques

It is important to have a good understanding of possible approaches to hyperparameter tuning to be able to efficiently make the correct decisions when it comes to tuning your network. Let’s take a quick look into why this is an issue, to begin with, and review the current techniques out there that you can use on your projects.

Read more

Which Deep Learning Library to Choose | Keras vs. Tensorflow vs. Others

If you ever ventured into the world of Deep Learning, you might have gotten stuck where many other people do: Which technology do I use? We have quite a few options of deep learning APIs but not all are suitable for first-time users. Let’s look into them one by one and decide on which one to use.

Read more

The famous bias and variance confusion

Bias and variance are some of the trickiest concepts to get a solid understanding of. It was explained to me a bunch of times and every single time after a couple of weeks I found myself thinking “Which one was which again?” So today, I’m on a mission to explain it to you in a practical way in hopes that this might be the last time you might need someone to explain it to you!

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How do machines learn: a simple explanation

By now you have probably heard this explanation: ML algorithms learn like humans. You give it examples and it recognizes and remembers the patterns in them. You need to give it a lot of examples, though, so that it can learn accurately. Okay, that’s clear. But HOW does it learn?

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How to build code you can be proud of as a data scientist

It is pretty much a stereotype that data scientists can’t write clean and understandable code. This doesn't have to be the case for you. By learning a few principles of how to write code properly, you can use the stereotype to your advantage and set yourself apart from the competition.

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Quick tips for career switchers who doesn't want to start from a junior position

When changing careers into data science, if you have years of work experience, it's only fair to expect a higher position than junior data scientist. In order to achieve it, you need to approach your job hunt differently than newly grads. Here are some tips for signalling to your future employer that you will bring value.

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Latest podcast episode

Take the Data Science Kick-starter course for free

And receive resources on becoming a data scientist sent right to your inbox
Enroll in the course now!