For quite some years you could find endless possibilities if you wanted to learn just with a click away. Datacamp is a part of that possibility and in this Datacamp Data Science Review, we will discuss the Datacamp Data Science Skills and Career Tracks courses along with their details.
A lot of people have chosen this path but there were a lot more that didn’t believe that learning online can be useful and if it came close to learning in a face-to-face class.
Following Covid-19, when all institutions and universities began offering online seminars and courses, the perception that online courses were actually rather good grew.
Finally, people found out that you can get a world-class level of education all around the world. The only too thing you would need was a computer system with the internet and your willpower.
That is practically what DataCamp stands for. They believe that everyone deserves access to high-quality education.
One of the biggest courses that they offer is Data Science.
Stay with us on this DataCamp Data Science review in order to learn more about its benefits and why DataCamp is the perfect place to learn it.
The Curriculum Team at DataCamp has created course programs (called ‘Tracks’) to help you navigate your Data Science journey and gradually develop complementary abilities.
They presently offer two types of Tracks in a range of programming languages: ‘Career’ and ‘Skill’.
As the respective names suggest the skill track includes short expert videos with immediate hand-on-keyboard exercises that have as a goal for students to acquire new skills fast.
Skill Tracks are a collection of two to seven courses that focus on particular complementing abilities in a variety of programming languages.
These courses and abilities may be incorporated in Career Tracks as well.
In this DataCamp Data Science review, we are going to talk about the Skill Tracks for intermediate-to-advanced programmers looking to learn certain abilities, such as Data Cleaning or Machine Learning that The Curriculum Team at DataCamp has created.
On DataCamp’s Data Science Courses you will find career tracks too on technologies like Python, R, or SQL.
A group of industry experts has hand-picked these career tracks that you can easily attend at any time.
After finishing these courses you will be ready with everything you need to know in order to start a new career in the Data Science field.
Starting with beginner courses that cover basic competencies (such as language syntax) and continuing to more specific, advanced topics (i.e. machine learning, network analysis, etc.), Career Tracks are our most complete option for Python, R, and SQL.
After learning some basic information about DataCamp in general I wanted to review more in detail two data scientist courses.
The reason why I choose these ones is that in my opinion, they are a good kick start in your career.
The courses that I’m talking about are Data Scientist with Python and R Career Track. Without further ado let’s learn more details about these two courses.
Firstly I must say that DataCamp’s Data Scientist With Python is super helpful filled with a lot of information, especially for beginners.
So if you are wondering how to advance should you be before taking this course, don’t you worry because it does not require any prior coding experience.
If you choose to take this course, you will learn every basic and intermediate integral skill that you will need to be an aspiring Researcher or Data Professional.
The best thing that you can expect from this course and from all the DataCamp courses for that matter are the interactive exercises.
The best way to learn is by doing it. Also, you will be going to learn and use different popular Python libraries including NumPy, pandas, Matplotlib, and many more.
Going through this course will give you a kick start on your journey to becoming a confident Data Scientist.
This is the other Data Scientist with an R career Track that is perfect to help beginners starting their journey on the right foot.
To help to make things easier for everyone in this course are implemented various quizzes, video tutorials, and interactive exercises.
This is a known way that helps to memorize everything way easier than the older way with just reading theory in some book.
Through interactive tasks, you’ll gain hands-on expertise with some of the most popular R packages, such as ggplot2 and tidyverse packages like dplyr and readr.
Then, using real-world datasets, you’ll master the Statistical and Machine Learning techniques you’ll need to develop your own functions and do Cluster Analysis.
After you finish the course you will get a certificate and a badge that you can showcase on your CV or LinkedIn. This is a great plus if you are thinking of getting a job or internship any time soon.
Obviously, Data Science courses and projects make a good part of the DataCamp course inventory . The DataCamp team has put a lot of effort to make a professional and easy to learn.
For most Skill and Career tracks, students can choose from numerous projects. These student projects are intended to assist you in developing a portfolio of work to show to possible employers.
Certificates of completion are good, but demonstrable hands-on experience is much better.
DataCamp projects are created and directed by Data Scientists from across the world. Take, for example, Rasmus Baath, who is in charge of five DataCamp Python projects.
He has headed data science teams at Activision Blizzard’s King Entertainment and Castle.io, a cutting-edge cybersecurity firm.
It’s a dream come true to be able to develop projects with the support of Competent Data Scientists like these.
In this DataCamp Data Science review, we are going to tackle every aspect in order for you to know everything you need even before starting it.
Now let’s talk about an important aspect of every online course, the pricing of it, and the timeline.
Different from other online learning platforms, like Udemy or Coursera, DataCamp is a subscription-based service with a number of different plans to choose from.
One of the three individualized plans is available to an individual learner. The Free account ($0), the Standard account ($25 per month), and the Premium account ($33.25 per month) are all available.
The Standard and Premium accounts are both invoiced annually, with the Standard membership being the most popular. A currency converter for pricing is located in the upper right corner (see image below), making it convenient for all users.
But besides the main personal plans, DataCamp offers Business plans too. The business plan is divided into two subcategories where you can choose.
On one hand, you have a Professional plan and on the other, you may choose an Enterprise plan. The professional plan is the most used of the two of them. It requires a minimum of 5 users and it will cost only $25 per user/per month.
The enterprise plan is for larger teams and organizations. It doesn’t have an exact price on the monthly cost per user. Anyone who is interested in it can contact DataCamp directly, and their team will create a custom plan based on your business needs.
Some of the biggest companies on the market right now have been working with DataCamp for a long time now. We can mention a few of them like Google, Uber, and eBay.
Check this out -> Datacamp Machine Learning Scientist with Python Review
You can cancel your monthly or annual subscription at any time and keep full access until the end of the month or year.
Also read: Lambda School Data Science review
So, let’s know about the Datacamp Data Science certifications in this Datacamp Data Science Review.
Certificates, sometimes known as Statements of Accomplishment, are available for all of DataCamp’s courses and tracks.
These can be added to your CV or LinkedIn profile to demonstrate to potential employers your enhanced knowledge and skills.
While the certificate’s intrinsic value isn’t especially great, the information and skills acquired during the process of receiving the certificate are.
Many genuine data scientists have finished dozens, if not hundreds, of DataCamp courses, thus a single credential will almost certainly not be enough to secure you a job in the field.
The Understanding Data Science course is in my opinion the best path to choose in order to get to know basic data science and full perception of what you can expect in this beautiful career.
The first lessons are about defining what data science is. Afterward, this course covers all the Data Science Workflow and how data science is applied to real-world problems.
By the end of this course, you’ll learn about the many Data Scientist positions, as well as core topics such as A/B testing, time series analysis, and machine learning, as well as how data scientists extract information and insights from real-world data.
So don’t let the jargon scare you away. Start studying and developing skills in an in-demand area, and see why data science is for everyone!
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DataCamp is, in my opinion, one of the best learning tools for Data Science. There are a number of reasons why I am confident in my assertion.
Especially for beginners and intermediate DataCamp has a lot of advantages.
Because of its Extensive collection of Data Science instructional resources, practical projects, and courses, DataCamp is well worth the investment.
While DataCamp is best suited and most worthwhile for beginners and intermediate-level students, it can also be valuable for experienced data scientists who want to learn new skills quickly.
Looking at the pros and negatives sections of this DataCamp review, it’s clear that I had a great overall experience with the platform.
There are a few minor flaws here and there that could be addressed. The entire DataCamp learning experience, on the other hand, was amazing.
I appreciated working with the web-based code editor (despite the fact that it typically wrote 90% of the code for me) and the website’s overall user-friendliness.
As a result, I heartily recommend DataCamp for learning R, Python, and SQL for Data Science and Analytics.
Today, whether public or private, almost every sector demands data science competence. Health and wellness, retail, web and application development, banking and finance, and governmental organizations are some of the top industries where data science is essential.Unders