DataCamp Machine Learning Review 2024: Is It Worth It?

Datacamp is an online learning platform that is popular for its interactive and beginner-friendly courses, especially for Data Science and Data Analytics. Datacamp is one of the most recommended online learning platforms for beginners and intermediate learners. In this Datacamp Machine Learning Review, we will cover all the details about the Datacamp Machine Learning courses.

An interactive learning environment like Datacamp covers data science-related subjects. Beginners and students looking for active content are drawn to the courses’ engrossing and concise design. Its courses and track programs emphasize pursuing new career choices and acquiring new skills. The platform uses subscription models with yearly or monthly billing that can be cancelled at any moment.

Most of the instructors at Datacamp are Data Science experts having extensive knowledge of Analytics. They offer a free plan which provides access to initial chapters of courses and assessments. Datacamp has a clear pricing plan for its courses and programs which we will discuss in this post later.

Datacamp has increased its course catalog and collection offering more than 350 courses relevant to programming, data science, and data analytics.

Today, Machine learning is on the boom, it the most popular buzzword in the world of Artificial Intelligence. Various students and tech enthusiasts are trying to learn and practice the concepts of machine learning and implement them into their projects and ideas.

But selecting the right Machine learning course online can be a hectic and confusing process and that’s the reason why in this Datacamp Machine Learning Review, we will be reviewing Datacamp’s Machine learning courses and programs extracting out various important points and insights. 

Some of the most popular Machine learning program’s of Datacamp which will be focused on in this post are –

1. Machine Learning Fundamentals with Python Skill Track
2. Machine Learning Fundamentals with R Skill Track
3. Machine Learning Scientist with R Career Track
4. Machine Learning Scientist with Python Career Track

What are Skill tracks and Career tracks?    

Datacamp broadly divides its courses on the basis of the tracks i.e the Skill track and the Career track.

Skill track is a collection of courses designed by experts and is meant to provide domain-specific expertise. The courses in the skill track are curated by industry experts that can help you a lot in developing your data skills. 

The courses in the skill track follow a guided series of videos along with interactive exercises. No prior coding experience is required in most of the courses available in the skill track.

Currently, DataCamp has 51 programs in its Skill track covering all the basics and the fundamentals of the Python and R programming languages. Various intermediate to advanced applications of those programming languages is also covered in this skill track. 

On the other hand, the Career track is slightly different from the Skill track. Courses and programs in the Career tracks are highly recommended to that student and professionals who want to advance in their career.

Career track as the name suggests is the career-building learning path having a collection of courses and programs that can help you a lot in developing your Data skills and take your next step advancing in your career. 

If you are serious about kick-starting your career in the field of Data Science or Analytics then the Datacamp Career track courses are enough to take you to the next level. 

The courses in the Career track also follow a guided series of videos along with interactive exercises. Prior coding or programming experience might be required in the courses available in the Career track.

At present, there are 12 programs in the Datacamp’s Career track. Selecting the career track course ensures that you are going through the courses selected by experts and will gain the knowledge of everything required for advancing in your Data Career.

We will specify the courses on the basis of the skill or the career track for more clarity in this DataCamp Machine Learning Review.

For learning and practicing the concepts and fundamentals of Machine learning the two popular courses in the skill tracks are – 

1. DataCamp Machine Learning Fundamentals with Python Skill Track
2. DataCamp Machine Learning Fundamentals with R Skill Track

And the other two popular courses available in the Career tracks are – 

1. DataCamp Machine Learning Scientist with R Career Track
2. DataCamp Machine Learning Scientist with Python Career Track

Details about DataCamp Machine Learning Courses

Now, it’s time to have a look at the top four DataCamp Machine Learning courses in this DataCamp Machine Learning Review.

1. Datacamp’s Machine Learning fundamentals with Python skill track.

So, this DataCamp’s Machine learning fundamentals with Python is a really popular course available in the skill track for learning the fundamentals of Machine learning with Python.

It’s a beginner-friendly course and is perfect for those who want to learn the fundamental concepts of Machine learning and be a part of the ML Revolution. 

There are overall 5 courses in this skill track – 

1. Supervised learning with Scikit-Learn
2. Unsupervised learning in Python
3. Linear Classifiers in Python
4. Case Study: School Budgeting with Machine Learning in Python
5. Introduction to Deep Learning in Python

2. Datacamp’s machine learning fundamentals with R skill track.

R is also one of the most popular programming languages used in Machine learning and analytics. In this course, you will learn the basics of prediction using Machine learning. 

This Machine Learning Fundamentals in the R Skill track will cover the prediction of categorical and numeric responses via classification and regression, along with unsupervised learning. 

In this Skill track, you will learn about processing data for modeling, training your models, visualizing your models along with accessing their performance, etc.

There are overall 4 courses in this Datacamp’s Machine Learning fundamentals with R as follows – 

1. Supervised Learning in R: Classification
2. Supervised Learning in R: Regression
3. Unsupervised Learning in R
4. Machine learning with caret in R

3. Datacamp’s Machine Learning Scientist with Python Career track

As we already discuss, the courses and programs of the Career Track are for individuals who want to grab a job in the field of Data Science or AI or the one who wants to advance in their professional career. 

In this Machine learning Scientist with Python career track, you will master the essential skills required to land a job or advance in the field of Machine Learning.

In this Career Track, you will learn various applications of Machine learning and how to implement them practically. You will learn how to process data for features, train your models, assess performance, and tuning parameters for better results. 

You will also get a brief introduction to Natural language Processing, Image processing along with popular libraries such as Spark and Keras. As this is the career track, it requires a lot of dedication and time to cover all the courses available in this Career Track.

There are overall 23 courses in this Machine Learning Scientist with Python Career Track and they are as follows – 

1. Supervised Learning with Scikit-Learn
2. Unsupervised Learning in Python
3. Linear Classifiers in Python
4. Machine Learning with Tree-Based Models in Python
5. Extreme Gradient Boosting with XGBoost
6. Cluster Analysis in Python
7. Dimensionality Reduction in Python
8. Preprocessing for Machine Learning in Python
9. Machine Learning for Time Series Data in Python
10. Feature Engineering for Machine Learning in Python
11. Model Validation in Python
12. Machine Learning Fundamentals in Python
13. Introduction to Natural Language Processing in Python
14. Feature Engineering for NLP in Python
15. Introduction to Tensorflow in Python
16. Introduction to Deep Learning in Python
17. Introduction to Deep Learning with Keras
18. Advanced Deep Learning with Keras
19. Image Processing in Python
20. Image Processing with Keras in Python
21. Hyperparameter Tuning in Python
22. Introduction to PySpark
23. Machine Learning with PySpark

4. Datacamp’s Machine Learning Scientist with R Career track

R programming language has a slightly different paradigm from the other programming languages which is the reason why it is practiced by various Data Science and Machine Learning enthusiasts all over the world. 

In this Machine Learning Scientist with R Career Track, you will combine your R programming skillset with the toolbox to perform supervised and unsupervised learning.

In this Career Track, you will learn how to process data for modeling, train your models, visualize your models by analyzing their performance.

In simple words, you will learn most of the things which will be taught in the Machine Learning Scientist with Python Career Track replacing Python with R programming language.

There are overall 14 courses in this Machine Learning Scientist with R Career Track and they are as follows – 

1. Supervised Learning in R: Classification
2. Supervised Learning in R: Regression
3. Unsupervised Learning in R
4. Machine Learning in the Tidyverse
5. Intermediate Regression in R
6. Cluster Analysis in R
7. Machine Learning with caret in R
8. Tree-Based Models in R
9. Machine Learning Fundamentals in R
10. Support Vector Machines in R
11. Fundamentals of Bayesian Data Analysis in R
12. Topic Modelling in R
13. Hyperparameter Tuning in R
14. Bayesian Regression Modelling with rstanarm

DataCamp Machine Learning Projects and Exercises

There is no Standalone project for the standard users which you will have to complete or develop on your own but there are a variety of exercises that will provide you practical knowledge essential for a student or Machine Learning professional to have. 

In each course available in the skill track there are various chapter’s or unit’s and in each chapter, a concept with its fundamentals will be taught to you, after that there will be a queue of exercises related to that concept in the same chapter which you will have to complete. 

Basically, those exercises are part of the project which you will be working on as a part of your learning. 

Let’s take an example to understand the exercises because elaborating them in this DataCamp Machine Learning Review will make it unusually long.

For example, if you opt for Datacamp Machine Learning Fundamentals with Python skill track then you will have to go through 5 different Machine Learning courses which the first course will be Supervised Learning with scikit-learn.

The first chapter of Supervised Learning with Scikit-Learn is “Classification”, in this chapter you will learn to classify problems and how to solve them using supervised learning techniques. 

After learning the basics and the fundamentals of Supervised Learning you will have to solve the exercises which are the cumulative project in the other words. In this chapter, you will have to apply your learnings to the political dataset where you will have to classify the party affiliation of United States congressmen based on their voting records.

So this was just an example of the exercises which you will go through in any of the skill or career tracks. A large number of exercises make sure that you practice a lot and gain a level of proficiency and confidence in Machine Learning.

Datacamp Machine Learning Pricing and Timeline

Now, let’s have a look at the DataCamp’s Machine Learning pricing and timeline in this Datacamp Machine Learning Review. There are overall four tracks of Machine Learning in Datacamp, two skill tracks, and two career tracks. The pricing of all the four-track is not different.

Datacamp follows a clear pricing plan for all of its courses, skill tracks, and career tracks. Pricing plans are broadly divided into two different types – 

1. Personal Plans
2. Business Plans

First coming to the Personal Plans, these plans are for students and professionals or individuals looking to learn and develop Data skills for any purpose or interest. 

Personal Plans are divided into three parts – 

1. Standard
2. Premium
3. Free

Standard Plan is the most popular pricing plan in which you will have to pay $12.42 per month billed annually. This plan will provide you all the essentials to grow your Data Skills. 

Premium Plan is for the learners who want to access all the projects. In the Premium Plan, you will have to pay $33.25 per month billed annually.

A Free plan is also there for the student who wants to try and explore DataCamp.

Business Plans are divided into two parts – 

1. Enterprise
2. Professional

Enterprise business plan is for the advanced integrations and reporting for large organizations. You can contact them here for approximate pricing.

The professional plan is for simple small team management. In the professional business plan, you will have to pay $25.00 per user per month which will be billed annually.

Coming to the Timeline of these Machine Learning programs, well you should be knowing that all of the courses, skills, and career tracks are self-paced. So it depends on you that how fast you finish up the courses.

But specifying the content duration of the course is important. So let’s know the content duration of these four courses one by one.

• DataCamp Machine Learning Fundamentals with Python Skill Track – 20 Hours
• DataCamp Machine Learning Fundamentals with R Skill Track – 16 Hours
• DataCamp Machine Learning Scientist with R Career Track – 57 Hours
• DataCamp Machine Learning Scientist with Python Career Track – 93 Hours

Must see – Codecademy vs Datacamp: Which is best to learn Coding in 2021? (Comparison)

Certificates of DataCamp Machine Learning courses

Certificates are the valuable credentials provided to the students and learners after completing a certain course or program, certificate is one of the most popular ways to showcase the required skillsets. 

DataCamp does not offer any accredited certificates after the completion of the course, skill, or career tracks. But it won’t be causing any problem because DataCamp offers a statement of accomplishment that acts as a certificate for the completion of the course of the program.

You will receive a similar Statement of Accomplishment as per your course or program. You can share that Statement of Accomplishment on Linkedin or any other platform in order to showcase your learned skills.

About the Instructors

DataCamp has over 250 expert instructors coming from the top universities and institutions such as Duke University, Oregon State University, etc. Instructors at Datacamp have good knowledge of the subject and often are subject matter experts.

On the home page of the course or the skill or the career track, you will get a block representing the list of instructors who will teach in that specific course. 

Hugo Bowne Anderson who is a Data Scientist at DataCamp, Benjamin Wilson who is the Director of Research at lateral.io, Mike Gelbart who is an instructor at the University of British Columbia, are common examples of expert’s instructor’s team at Datacamp.

Pros and Cons of Datacamp’s Machine learning courses

There are various online learning platforms that can help you in understanding the fundamentals and concepts of Machine Learning. 

That’s the reason why it is important to know the reasons why to choose DataCamp for Learning Machine Learning and why not to choose it.

So, let’s uncover the pros and cons of the DataCamp’s Machine Learning courses, skills, and career tracks in this elaborative DataCamp Machine Learning Review.

Pros – 

1. DataCamp has an expert team of Instructors from the Data Science and Analytics community.
2. Courses and programs have an interactive learning methodology which is as follows – 
3. Assess – You can test your skills and track your progress
4. Learn – Interactive courses which you can complete self-paced
5. Apply – You will solve real-world problems
6. Practice – You will practice quick daily challenges
7. DataCamp has a clear pricing plan which is pretty much self-descriptive.
8. DataCamp has grown its course catalog and now a total of 354 courses are available on the platform covering various topics of Data Science, Machine Learning, and Analytics.
9. DataCamp also provides a free plan by which you can give Datacamp a try and explore its features.
10. DataCamp Mobile App is available for iOS and Android.
11. DataCamp has a nice and beginner-friendly User Interface. 

Cons – 

1. DataCamp does not provide any accredited certificate. 
2. Their state of accomplishment credentials is not associated with or recognized by any university or institution.
3. Premium plans can be a bit costly for students who want to explore the world of Data Science.

Conclusion – Does Datacamp’s Machine learning courses worth it.

Datacamp has become one of the most recommended online learning platforms for learning various Data Skills. Machine Learning skills and career tracks have an expert-selected collection of courses and are loved by various Data Science and Machine learning enthusiasts all over the world. 

DataCamp has served over 85,00,000 students with their quality content and exercises. The machine learning Career track can be quite difficult and require a level of dedication and time in order to get completed but in the end, it provides a proficient level of knowledge in the field of Machine Learning.

So, that was all in this Datacamp Machine Learning Review, let us know in the comment what do you think about the DataCamp Machine Learning courses.