DataCamp Data Scientist with Python Review

When the quarantine because of Covid-19 started, I had a lot of free time. It was been more than three years since I finished university, and since my last class too. I thought to myself that it will be a great idea to take some lessons and learn a new skill. I enroll in the DataCamp Data Scientist course and in this DataCamp Data Scientist with Python Review I will share my views along with the details of the course. 

After asking around I finally choose to go for the Data Scientist with Python Career Track on Datacamp. 

If you want to start a course for yourself, I believe that you will have a clear idea in the end on what to expect from the Data Scientist with Python Career Track. 

Why haven’t you been able to learn Data Science With Python yet?

I understand that you might feel stuck. You’ve given it a lot of thought and you’ve even started learning about it. But the truth is that you haven’t gotten very far. 

I can feel you completely. After I finished studying Data Science, I was in a similar place as you are now. 

Furthermore, a number of my friends, juniors, and blog followers have shared with me their reasons for not being able to make it as a Data Scientist.

Let me tell you that despite your desire and desperation, there are just two reasons why you haven’t yet become a Master in Data Science. 

Either of the following two explanations may apply to you:

• Your learning isn’t well-structured.
• Don’t practice in small increments.

Either we don’t commit to a single learning resource (a course or a book) and end up scrounging from other sources. 

Alternatively, we may choose not to use any structured learning resources at all and instead study in bits and pieces via YouTube or other blogs. 

Here in this DataCamp Data Scientist with Python Review, I will explain how Datacamp will help you…

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DataCamp as a learning platform

What is DataCamp?

Belgian data scientists Jonathan Cornelissen, Martijn Theuwissen, and Dieter De Mesmaeker founded DataCamp in 2014 as an online learning platform for Data Science. 

For hands-on coding training, DataCamp offers online classes that employ a web-based code editor. The majority of DataCamp’s courses are in R, Python, and SQL.

How does DataCamp Work?

On its online learning platform, DataCamp provides corporations and individuals with hands-on coding classes. 

Learners on DataCamp put their skills in Data-related topics to the test in order to improve and maintain their Data fluency. 

The site focuses almost entirely on courses related to Data Science and R programming. 

As they explain, more than 90% of the world’s data has been created in the last two years, implying that data-savvy specialists are in greater demand than ever before. 

R, Python, and SQL are the primary programming languages taught at DataCamp.

Data Scientist with Python Career Track. What’s it about?

Let’s know what actually this DataCamp Data Scientist with Python Career Track is in this DataCamp Data Scientist with Python Review.

The main goal of Data Scientist with Python Career Track is to help you pick Data and extract meaningful information out of it. 

This should help you impress bosses and make Data-driven decisions rather than merely intuitive ones. 

If you’ve ever wondered “how to become a data scientist with Python,” this is the best place to start. 

This Career path consists of 23 courses (out of the 300+ we mentioned above).

This career track is dedicated mainly to beginners that want to start a career in data science. 

There is no need to have any prior coding experience. 

This class will teach you how to use this versatile language to import, clean, manipulate, and visualize data, which are all essential skills for any aspiring data professional or researcher. 

You’ll acquire hands-on experience with some of the most popular Python libraries, such as pandas, NumPy, Matplotlib, and others, through interactive activities. 

DataCamp Data Scientist with Python Course Timeline

Coming to the course Timeline in this DataCamp Data Scientist with Python Review, this Data Scientist with Python Career Track is filled with a lot of useful lessons and hands-on tasks. 

It has 88 hours of work that is divided into 23 courses. 

But besides all this, you will have to complete 6 projects in order to put into action everything that you have learned so far. 

How long does it take to finish the Python Data Scientist track at DataCamp? 

According to their Website, it will take 88 hours. Despite the fact that this is the entire time allotted for the video content, practice, and exercises. 

It is timed for people of various levels of experience, so if you are comfortable with the lessons, you can complete them in much less time.

Introductions into Python Basics

For starters on this career track, you will be widely introduced to the concepts of Python. 

You will learn to do the basic Python functions by using a script. As soon as you get comfortable with Python’s basic data types, you will create your first variables. 

Second, the XP or experience point grading system is quite good. The combination of a sense of accomplishment and learning has a significant influence! 

Hugo, the instructor, gives a brief overview of the course in the first video for “Hello Python.” 

A good aspect is the clear User interfaces with simple access to information for the learning materials.

Getting Past Python Basics

As you progress through the fundamentals, the next few parts become increasingly focused on Data Science. 

The foundation of the field, for example, is playing around with datasets using NumPy, Pandas, and other tools (which DataCamp also supplies).

There are 23 such courses in the Data Scientist with Python track. 

You’ll quickly improve your skills and be working on real-world datasets in no time, just like we did with the previous one. 

Here’s a quick rundown of what you’ll learn in each of the other courses:

• Python isn’t just for beginners. With the “Intermediate Python” course, you may delve deep into its complexity.
• For any Data Scientist, Pandas is a must-have tool. To learn each notion, learn how to play around with it and act on some data.
• Matplotlib and Seaborn are great libraries for plotting and visualizing data to help higher-ups make decisions (that you’ll enjoy doing).
• Python for Data Science is not the same as regular Python. Look at what tools you have and how you can use them to save time while dealing with data.
• Statistical thinking will assist you in thinking statistically and improving your statistical inference skills.
• You’ll study more about supervised and unsupervised algorithms, as well as how they make up the majority of what we call Artificial Intelligence, in this course.
• And there’s so much more!

Pros & Cons of the Data Scientist with Python Career Track

Now, let discuss some of the pros and cons of the DataCamp Data Scientist with Python Career Track in this DataCamp Data Scientist with Python Review.

Pros of the Data Scientist with Python Career Track:

• One of the biggest pros that this course has is interactive learning with videos, programming exercises, and different projects.
• Learning to solve real-world projects, work in datasets and problem sets. 
• To teach and create the courses, renowned professors with extensive academic backgrounds are used.
• Big community support from everywhere on the web via blogs, Slack channels, and forums.
• In comparison to different learning platforms where you have to pay for every course that you have to take, DataCamp will charge only a low cost for subscriptions.

Also read: Lambda School Data Science review

Cons of the Data Scientist with Python Career Track:

• The exercises have pre-written code in the environment, which discourages you from writing your own.
• The datasets are incredible and based on real-life scenarios, however, the activities lack the same practicality.

Which Datacamp subscription to choose from?

Considering everything else, the price may become the real deal-breaker for some which is why we dedicated a part to this article. 

So without further ado let’s get started. 

As we said earlier Datacamp, different from most of the learning platforms, works with subscriptions fees. 

On most of the other platforms, you will have to pay for every course you take. 

But on the Datacamp website, all you need to do is to choose one of the subscription plans they have and you are ready to choose what course you like. 

Premium – $49 or $33.25 per month

The monthly subscription plan is somewhat more expensive ($49 per month) than the yearly subscription plan ($33.25 per month). 

In contrast to the monthly billing option, paying yearly saves $189 over the course of a year.

Standard – $29 or $25 per month

The Standard plan will cost you $29 per month ($348 per year) if you pay monthly. 

When you pay yearly, the Basic plan is $25 per month ($300 per year), which saves you $48 over the monthly plan. 

DataCamp offers a variety of incentives on their subscription levels from time to time. 

Sales frequently feature a 50% discount on the annual fee, which is well worth it! When DataCamp’s new deals go live, I’ll post them here.

Free – $0 per month

The Free plan, as its name implies, is completely free to use. A free DataCamp account can be created by anyone. 

This will merely give you an idea of what the platform is all about, but it is quite limited in terms of functionality.

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Conclusion: Do I Recommend It?

To wrap up this Data Scientist with Python Career Track review, let’s return to the original question: is DataCamp worth paying for?

Yes, I believe so!

However, to make the most out of it, it will take a lot of dedication, in order to get something out of it. 

More online courses are now offering interactive shells so students may start coding right away, but it is still important to emphasize for beginners. Nothing stops a novice from learning faster than difficult debugging before they’ve even gotten started. There is no doubt that Datacamp has worked hard to make the learning process easy and enjoyable.

It is not enough just to buy a subscription and wait for things to happen. But I guess that you all know that. 

So do not lose more time and put some effort into it. Your bright career in Data Science is waiting for you.