Wiley  Mayer

Wiley Mayer


Top 5 Programming for Data Science and Machine Learning in 2021

If you want to learn Data Science and Machine Learning in 2021 but not sure which programming language to choose then you have come to the right place. Earlier, I have shared, best Data Science courses for beginners as well as free Data Science and free Machine learning courses, and in this article, I am going to share the b_est programming languages you can learn for Data Science and Machine learning in 2021.

Data Science is an exciting field and more and more programmers are aiming to become Data Scientist but one question often puzzles them is which programming language they should learn for Data Science? Many of them confused between popular Data Science programming languages like Pythonand R, and some people like Java developers ask me a lot if they can use Java for Data Science or not.

Being an author of a Programming blog, I have asked this question many times and I finally thought to put together my thought in written form as an article.

I have also been sharing the best programming languages for quite some time also and in the past, I have shared the best programming language for web development and mobile app development, if you haven’t checked them then you can also check them if you wish to become a web developer or mobile app developer in 2021.

In order to choose the best programming language for Data Science, you need to first know what do Data scientists do in their day-to-day job? Because that’s what make difference. If you choose the wrong language then you will suffer in productivity and performance and that can impede your career growth.

One of the most common tasks for Data Science is to procure data, clean them and massage them so that it can be analyzed. More often than not, you need to write a quick script to do this job and for that, you need a programming language that has the right tools and allows you to do this job in few lines of code.

At the same time, you don’t want to choose a programming language with poor performance because time is critical and you often need to process a large amount of data. If your script is taking days to process the data then it won’t help much.

Keeping all these things in mind, here is a list of the best programming languages for Data Science.

#python #machine-learning #data-science #java #sql

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Top 5 Programming for Data Science and Machine Learning in 2021
Uriah  Dietrich

Uriah Dietrich


How To Build A Data Science Career In 2021

For this week’s data science career interview, we got in touch with Dr Suman Sanyal, Associate Professor of Computer Science and Engineering at NIIT University. In this interview, Dr Sanyal shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.

With industry-linkage, technology and research-driven seamless education, NIIT University has been recognised for addressing the growing demand for data science experts worldwide with its industry-ready courses. The university has recently introduced B.Tech in Data Science course, which aims to deploy data sets models to solve real-world problems. The programme provides industry-academic synergy for the students to establish careers in data science, artificial intelligence and machine learning.

“Students with skills that are aligned to new-age technology will be of huge value. The industry today wants young, ambitious students who have the know-how on how to get things done,” Sanyal said.

#careers # #data science aspirant #data science career #data science career intervie #data science education #data science education marke #data science jobs #niit university data science

sophia tondon

sophia tondon


5 Latest Technology Trends of Machine Learning for 2021

Check out the 5 latest technologies of machine learning trends to boost business growth in 2021 by considering the best version of digital development tools. It is the right time to accelerate user experience by bringing advancement in their lifestyle.

#machinelearningapps #machinelearningdevelopers #machinelearningexpert #machinelearningexperts #expertmachinelearningservices #topmachinelearningcompanies #machinelearningdevelopmentcompany

Visit Blog- https://www.xplace.com/article/8743

#machine learning companies #top machine learning companies #machine learning development company #expert machine learning services #machine learning experts #machine learning expert

Cyrus  Kreiger

Cyrus Kreiger


How I'd Learn Data Science If I Were To Start All Over Again

A couple of days ago I started thinking if I had to start learning machine learning and data science all over again where would I start? The funny thing was that the path that I imagined was completely different from that one that I actually did when I was starting.

I’m aware that we all learn in different ways. Some prefer videos, others are ok with just books and a lot of people need to pay for a course to feel more pressure. And that’s ok, the important thing is to learn and enjoy it.

So, talking from my own perspective and knowing how I learn better I designed this path if I had to start learning Data Science again.

As you will see, my favorite way to learn is going from simple to complex gradually. This means starting with practical examples and then move to more abstract concepts.

#data-science #machine-learning #artificial-intelligence #python-top-story #data-science-top-story #learn-python #learn-data-science

5 stages of learning Data Science

With recruiters listing a myriad of “preferred skills” in their job postings, learning Data Science can get quite overwhelming at times. Dividing the journey up into five chapters can provide a clearer picture of what lies ahead.

#machine-learning #learn-data-science #data-science-training #python-for-data-science #data-science-courses

5 Data Science Podcasts To Follow in 2021

If we only learn data science through a rigid curriculum created by universities or online courses from Coursera or Udemy, we may find the learning process too boring. If you ever find yourself losing motivation in this long journey of studying data science, you may just need some podcasts to break the routine and get some inspiration. The major difference between these two approaches of learning is that the former focuses on theory and concepts, whereas the latter introduces more practical experience and projects that add flesh to the bones.
Listening to podcasts is a great way to absorb knowledge while you are commuting or doing the chores. One of the amazing apps that I recommend using is called “Airr” which allows users to highlight the content of the podcast and transcribe the highlight into notes. This tool is especially useful for technical podcasts since information is more easily erased if you are more of a visual learner than an auditory learner. Therefore, putting it into notes somewhere would assist in transforming them into long term memory.
On the other hand, if you are more of a visual person who prefers to learn through reading, then have a read of the Data Science website list that I curated :)

#data-science-inspiration #data-science-podcast #learn-data-science #data-science #data-science-resources