Working with data is moving today from some trendy thing towards the necessity for specialists from different domains. There are many ways to gain the skills of effectively working with big data sets but right now we will focus on a huge fish – DataCamp. In this review, we’ll see whether Datacamp is worth it and the needed details about this company.
- Good for beginners
- Low price
- Possibility to easily switch from one course to another (e.g. from SQL to Python)
- Constant updates of the content
- Convenient interface for practice, no special software is required
- Many projects
- May not be good for middle or advanced users
- Some exercises are too easy
- Customer support
“Learn data science today and apply it tomorrow”
What is Datacamp?
This is an online company that has gathered different data-related courses in one place. The provider has various classes mainly on R, Python, and SQL but also there are classes on Spreadsheets, BI, Tableau, and other topics. Those courses can be taken separately or as a set in frames of skill tracks or career tracks (read below about those formats).
In a nutshell, the company includes more than 340 courses which are a combination of videos with practical assignments, over 50 curated learning paths, and more than 50 real-life projects.
As for its features, DataCamp offers skill assessments where you can measure what is your current level of a particular skill. Also, the company has its mobile app (available on App Store or Google Play) where one can practice everywhere with their daily 5-minute coding challenges.
Who Is Datacamp for?
While DataCamp courses can be good for anyone, they will be the most beneficial for the following three groups:
- People who are planning to start a data-oriented career as a Data Scientist, Data Analyst, or Python Software Developer.
- Those who want to improve skills in related fields like online marketing – so that you can better analyze, visualize, and report marketing data as well as make data-driven decisions.
- People who just need to improve certain skills needed to become more proficient in working with data (for instance, for Digital Analysts who need to gain or improve knowledge of BI or Tableau).
All in all, this e-learning provider works best for beginners and intermediate-level students.
On Datacamp, you can choose among 3 learning formats to learn data-related skills.
- Courses – short 3-4 hours programs focused on a specific narrow topic.
- Skill Tracks – longer programs that consist of a series of courses.
- Career Tracks – the longest form of learning which includes a number of courses and made to prepare you for a new career.
How to use Datacamp
- Choose a course
First, you should decide on the technology to learn (R, Python, or SQL). Then, you can browse all the content related to it. For instance, if you’re interested in Python go to Products in the menu and then by choosing Python under the Course Catalog section. Then, you will be taken to the page, where you can choose either a skill track, which is a longer form of content, or a course, which is a shorter form of learning.
2. Choose a plan
Then, you need to buy a Datacamp plan to be able to access all the content you need. You can do it from a course page directly or by clicking on Pricing in the menu.
Check out DataCamp courses.PYTHON, R, SQL & MORE
Datacamp Career Track Review
Career track is a set of courses in a specific domain so that a person can learn new skills from scratch so to start a career. On datacamp.com, you can switch between three technologies – Python, R, or SQL and choose one of 14 career tracks. Among them are Python or R Programmer, Data Analyst, Data Scientist, Statistician, Machine Learning Specialist and some other programs.
Each track includes 15 single classes and takes on average 70 hours to complete.
Each class consists of a number of exercises. After starting the track, on the left side of the screen, you will see the information on the topic as well as the task you need to do; on the right side, there will be a console for writing the code. Here is how it looks like.
Datacamp Skill Tracks
Furthermore, you can search for a skill track. This is also a set of courses but a shorter one. You can choose one of 50 skill tracks of approximately 15 hours’ duration each. Those programs cover also Python, R, or SQL, however, here additionally are courses on spreadsheets, shell and some theoretical issues.
For illustration, such tracks as Statistical Fundamentals, SQL Fundamentals, Image Processing, Applied Finance, Importing and Clearing Data, Programming with R or Python are on the list of Datacamp skill tracks.
Datacamp for Business
The company offers solutions for employees who want to improve the data skills of their teams. This subscription allows creating custom learning paths and features tools for measuring the team’s progress as well as creating reports on that.
Here you can request a free demo.
Datacamp offers two types of pricing packages – for individuals and for teams. Individual customers can choose between three subscription options:
- Free (includes intro parts (up to 7 first levels) of all courses, 3 sets practice challenge, and 1 skill assessment)
- Standart which costs $12.42 per month (includes all courses as well as skill or career tracks)
- Premium subscription which is $33.25 per month (additionally includes 80 projects to practice skills, content on Tableau, Power BI, and Oracle as well as priority support).
Basic business plan (for teams) costs $25 per user per month and requires at least five users for a subscription.
Datacamp Python Review
Here you can find all the Datacamp Python Courses, Skill Tracks, and Career Tracks.
Now, let’s see what you can choose from among each of them.
DataCamp Python Skill Tracks
There are 17 skill tracks focused on Python on Datacamp. You can find them by clicking on See all skill tracks (51) in the Products tab of the menu; then choose Python in the filter on the page.
Here is the list of all the 17 Pyhton skill tracks with additional information on each.
|Name||Courses included||Hours to complete||Description|
|Python Fundamentals||4||15||Manipulating dictionaries and DataFrames, writing Python functions, basics of data visualization.|
|Python Programming||6||24||Focusing on optimizing code, writing functions, and unit tests.|
|Importing & Cleaning Data||5||17||Importing and cleaning data as well as working with APIs and web data.|
|Data Manipulation||4||16||Using pandas, transforming, sorting, and filtering data in DataFrames.|
|Machine Learning Fundamentals||5||20||Basics of Machine Learning with information on prediction, pattern recognition, and the beginnings of Deep Learning.|
|Deep Learning||5||20||Working with neural networks using Keras, TensorFlow, and PyTorch libraries.|
|Time Series||5||20||Using pandas, NumPy, and Matplotlib to manipulate, interpret, and visualize time series data in Python.|
|Statistics Fundamentals||5||19||Evaluating statistical models, simulating data, and drawing data-based conclusions.|
|Data Visualization||5||20||Learning to work with Python data visualization libraries.|
|Image Processing||3||12||Learning image pre-processing and advancing to deep learning.|
|Python Toolbox||5||20||Learning techniques for handling missing data and datetimes, learning regular expressions for using in Python code.|
|Big Data with PySpark||6||24||Learn Apache Spark with Spark Python API.|
|Natural Language Processing||6||25||Fundamentals of natural language processing, learning how to transcribe and extract information.|
|Deep Learning for NLP||3||12||Working with natural language processing using scikit-learn, TensorFlow, Keras, and NLTK.|
|Marketing Analytics||7||28||Analyzing marketing campaigns and social media data, using machine learning to predict customer behavior.|
|Finance Fundamentals||6||25||A basic course that shows how to use pandas, NumPy, statsmodels, and pyfolio libraries to make data-driven financial decisions.|
|Applied Finance||4||16||Includes evaluating portfolios, calculating credit risk, and creating GARCH models to forecast volatility.|
DataCamp Python Career Tracks
Career Tracks are long programs designed to prepare a person for a new career. There are 5 career tracks on DataCamp which are focused on Python skills.
- Data Analyst (16 courses | 62 hours). Focused on data analyst skills to prepare, analyze, and present data.
- Data Scientist (23 courses | 88 hours) It covers basic Python topics like data types and functions and then proceeds to more data-focused ones like Data manipulation with Pandas, Data Visualisation with Matplotlib and Seaborn. The track also includes classes on Statistics and Machine Learning.
- Python Programmer (16 courses | 63 hours) Learning topics from data manipulation to unit testing.
- Machine Learning Scientist (23 courses | 93 hours) It shows how to train models, evaluate their performance and improve or customize it by tuning parameters. This track also covers such topics as NLP, working with images and using Spark and Keras.
- Data Engineer (25 courses | 95 hours) – Business-oriented program that shows how to efficiently ingest, manage, and warehouse data.
This program includes 23 courses and takes about 88 hours to complete it. It covers basic Python topics like data types and functions and then proceeds to more data-focused ones like Data manipulation with Pandas, Data Visualisation with Matplotlib and Seaborn. The track also includes classes on Statistics and Machine Learning.
This program provides 7 projects for practicing.
You don’t need to have any prior programming experience for enrolling.
This career track runs 93 while consisting of 23 single courses. This program is aimed at teaching how to train models, evaluate their performance and improve or customize it by tuning parameters. This track also covers such topics as NLP, working with images and using Spark and Keras (Python libraries).
Datacamp Python Courses
Generally, there are 145 Python courses and 48 Python projects. You can choose the needed one by choosing Python as Technology in the filter and then, choose the topic itself. On Datacamp you can find such Python topics as Importing & Cleaning Data, Probability & Statistics, Machine Learning, Applied Finance and others.
Here are just some of the examples:
- Data Manipulation with pandas
- Statistical Thinking in Python
- Machine Learning with Tree-Based Models in Python
- Introduction to TensorFlow in Python
- Web Scraping in Python
And many more
Here are some examples of Python projects:
- Classify Song Genres from Audio Data
- Predicting Credit Card Approvals
- Comparing Cosmetics by Ingredients
- A Network Analysis of Game of Thrones
- Give Life: Predict Blood Donations
How good is Datacamp for Python?
Datacamp is one of the best e-learning platforms to learn Python as it offers a huge variety of Python topics, projects, and a handy interface for practicing. However, the courses seem to be the most useful for beginners and might not be as good for advanced Python programmers.
Moreover, if your goal is becoming a data scientist or a data analyst, Datacamp is good at teaching practical skills like programming itself but you won’t learn other skills like critical thinking needed for this job.
Datacamp R review
This career track runs 76 hours and consists of 19 courses. It shows how to effectively work with data – structure, import, clean, or visualize it. It also touched statistical and machine learning techniques as well as the most popular R packages.
Among other R career tracks are R Programmer, Machine Learning Scientist with R and others.
Datacamp SQL Review
One of the best programs to become acquainted with this technology is SQL Fundamentals, a skill track that includes 5 courses and lasts 21 hours. This track shows what SQL is, how to join and perform other actions with data. Moreover, it teaches how to work with data in PostgreSQL.
Among other skill tracks focused on SQL are two: SQL Server Fundamentals and SQL Server Toolbox.
Other popular courses to consider
Here are also some good examples of single courses. Each one lasts for 4 hours and includes the first free chapter.
This course shows how Modern Portfolio Theory can be applied to the financial crisis of 2008, discusses Value at Risk (VaR) and Conditional Value at Risk (CVaR) as risk measures, present how Monte Carlo simulation can be used for predicting uncertainty, and also reveal how to utilize neural networks for risk management.
During this course, such Python libraries as pandas, scipy, and pypfopt and others will be used.
This class is part of text mining and it reveals how to identify emotional intent and divide text (e.g. reviews) by positive and negative language markers. This course also includes a case study where you can analyze Airbnb reviews, are they positive or negative ones.
This one is useful to learn new Excel functions to work with data. The course covers 35 functions like VLOOKUP and AVERAGEIF(S). It also includes training on the data.
How to Choose a Course on DataCamp?
There are so many courses on Datacamp that it might be hard to make a choice. Here are some tips to consider:
- Start with a short course. If you have no prior knowledge, start with Introduction to Python, a free basic course.
- If you have some prior knowledge but don’t want to dive into a specific field, pick courses like Intermediate Python, Object-Oriented Programming in Python, or Writing Functions in Python.
- If you are planning to work as a data analyst or data scientist, start with basic courses like Introduction to Data Science in Python, Data Manipulation with pandas, or Cleaning Data in Python.
- If you have a specific field of interest like Marketing or a specific task like scraping a website, choose courses accordingly (e.g. Analyzing Marketing Campaigns with pandas or Web Scraping in Python in this case).
After inspecting the feedback from clients, there are two main opinions. First, clients talk about the high quality of the courses. Second, customers complain about the renewal of the paid subscription and poor customer support.
Also, some customers with already a high level of skills claim that this e-learning provider is not that useful for them. However, beginners say Datacamp classes are good for them to gain the needed knowledge.
So, here are some examples of DataCamp reviews from Trustpilot, Quora, and Reddit.
“DataCamp is based on practice, it has a lot of practice assignments that gives you hands-on experience and it is advised to be taken after you have done your theoretical study in this field, after which you will be able to practice what you have learned.”
“Datacamp courses are light, short and straight to the point; I would call them “topic classes”. They include short videos, online coding that act as quizzes, and slides. They do not have much interaction or consultation forums.”
“It gently introduces you to a wide range technologies and subjects including GIT, Scala, Python, R, SQL, Tableau, Excel, Data Science, Machine Learning, Statistics and Probability and more… [But] The courses are really only intended for beginners.”
So, here is a brief recap of the pros and cons to answer the main question – is Datacamp worth it?
What is Good: DataСamp Pros
- It’s good for beginners, DataCamp courses don’t require any prior experience or education.
- You don’t need to install any special programs (like Pycharm for working with Python).
- You can easily switch from one course to another (e.g. from SQL to Python). This is good if you hesitate about which programming language is the best for you to learn.
- The price of the subscription is low, its courses are cheaper than the similar ones by competitors.
- There are constant updates of the content. There are new courses coming out almost every month (for example, the latest ones are “Introduction to Data Visualization with Plotly in Python” and “Hypothesis Testing in R“).
What is not good: DataСamp Cons
- If you are not a complete beginner, many courses might be too easy for you. Many exercises require you to just fill in the blank spaces or provide you with similar tasks.
- Sometimes, there might occur problems with paying for the subscription; when you don’t realize that you have been charged.
- Customer support may not answer your questions immediately or just ignore your requests.
How to use Datacamp effectively?
It might seem obvious but not all DataCamp subscribers use the platform effectively. Therefore, here are some tips to get the most out of it.
- Don’t start a few Datacamp courses at a time. This might lead to losing focus and quickly feeling overwhelmed.
- Set timeframes to finish the Datacamp course, Career track, a project, etc, and define clear skills you need to have after completing it. You can use DataCamp’s Assessments to check your progress.
- Make sure to find your own data-related project to implement learned skills. You should feel a strong need to improve your skills and be able to solve particular problems.
You can use the platform for free and get access to the first chapters of the courses and a few projects.
To do this, you need to click on your name on your profile photo. Then, choose ‘Subscriptions’ and ‘Stop Automatic Billing’ and confirm the action.
If you are interested in lower prices, right now, Datacamp doesn’t have any promo actions; however, sometimes the company offers such (this happens approximately every 2 months or before the holidays).
To join Datacamp for free, you just need to sign up with your email, choose the course, and enroll. However, you will have access to the introduction part only at no charge.
Yes, the company offers value for money and is able to teach you basics of R, Python, SQL or some narrower concepts.
The company currently offers only one certification, Data Science Professional.
While Datacamp certificates are not recognized, you can add them to your resume or Linkedin page as proof of skills.
Dataquest vs Datacamp
The companies offer very similar solutions, so Dataquest seems one of the main Datacamp competitors.
To start with, both Dataquest and DataCamp offer materials on three basic topics, Python, R, and SQL for working with data. However, Datacamp has a wider list of courses and learning formats. Dataquest provides 24-week data science courses while Datacamp has a course duration that varies.
Moreover, when comparing Datacamp vs Dataquest pricing, the first provider has a free basic plan while all subscription packages by Dataquest are paid starting from $49 per month.
As for similarities, both DataCamp and Dataquest include coding challenges and project-based training. Also, both companies have active community and support.
In a nutshell, DataCamp and Dataquest offer similar solutions. However, there are some aspects of why you might choose DataCamp when deciding
Codecademy vs Datacamp
Codecademy has a wider focus when it comes to the list of courses offered. Particularly, there are programs on a bunch of different programming languages for different goals while Datacamp has only R and Python classes for the main purpose – working with data. However, Datacamp lets you dive deeper when it comes to data science or data analysis.
Meanwhile, both online companies offer two types of learning, career paths (in Codecademy or tracks in Datacamp) which consist of more courses and therefore take more time to complete and skill paths (skill tracks) which are a shorter set of classes.
As for the price, both providers have a free basic subscription plan. As for paid ones, Codecademy offers a cheaper package at $16 per month.
Check out the full Codecademy review.
Datacamp vs Udacity
Udacity has more topics covered in the courses; however, it’s also much more expensive than Datacamp. For instance, the Data Analyst program costs $1436 for 4 months. However, Udacity also has more perks like technical mentorship and career coaching as well as some others.
Check out the full Udacity review.
Is DataCamp worth it?
After reviewing all the aspects, it seems that the Datacamp subscription is worth paying for it. Generally, the provider gives more benefits for beginners than for professionals but it depends on the course. All in all, it’s a narrow-focused online company (which often highlights its proficiency in the domain) that is a good choice in terms of value/money.
Disclosure: Self-Starters team has not received any compensation from Datacamp or anyone else associated with the company. However, this review contains affiliate links, which means that, if you click & purchase from these links then, we will receive a small commission. This commission helps us to maintain this website. But you don’t pay anything extra.