15+ Best DataCamp Courses & Certifications Online in 2023
Datacamp is a very popular destination for picking up some ninja skills in data science.
In fact, it boasts having trained data engineers who currently work in some of the most prestigious tech companies and startups.
However, does that mean that Datacamp is right for you? And, which are the best courses for launching a successful data science career on this platform…considering not all courses are created equal?
To begin with, if you are a complete beginner you’ll find Datacamp amazing because it has very interesting, laid back introductory courses for R, Scala and Python, the core languages for data analysis and visualization.
Once you pick up speed, you’ll be introduced to more advanced concepts in machine learning, Python libraries, data visualizations tools like Power BI and Tableau, but most importantly, case studies to test your skills.
In this article, we’re going to look at the best Datacamp courses and certifications to take in 2023.
Let’s get started.
1. Introduction to R
R is one of the most popular programming languages for data science projects apart from Python programming.
So if you’d like to launch a successful career in data science and artificial intelligence, I think you should consider learning both of these languages. They will open more doors of opportunities for you in the workplace.
This is one of the best Datacamp courses in 2023 for learning R programming.
In this course, you’ll get a proper introduction to R programming where you’ll get to master the basics of this popular open source language.
You’ll start off with the basics in vectors, factors, lists, and data frames. Once you nail the foundational concepts of R, you’ll be equipped with the skills you need to undertake some interesting data analysis projects in R.
Other topics you’ll cover include matrices where you’ll explore the different ways of creating matrices so that you can perform basic computations using them.
2. Introduction to Python
Like I mentioned earlier, Python and R and the languages to learn if you want true success as a data scientist today.
Python is a general purpose, open source programming language that has been rated the most popular programming language year over year. It’s used in web applications, APIs, Linux desktop applications, and data science libraries, just to name a few.
In this introduction to Python course on Datacamp you’ll pick up the very basics of Python so that you can build simple programs in it.
This way, you’ll build the foundation you need to then advance into more advanced features that are adapted to data analysis.
What’s more, this course focuses on teaching Python specifically for use in data science. So you’ll learn the various ways to store, retrieve, and manipulate huge data sets in Python.
You’ll also cover some popular data science tools to help you begin your data analysis journey.
3. Introduction to SQL
Structured Query Language based databases have been the traditional way of storing data for quite some time. But recently, the introduction of alternative NoSQL solutions has shaken its dominance a bit.
That being said, relational databases are still a must have skill if you are looking for a bright future in your data science career.
Here is another one of the best Datacamp courses for learning how to wrangle and extract data from SQL databases so that you run analysis models on them.
You’ll begin by covering the basic syntax of SQL that many databases implement. Some of the popular SQL databases include PostgreSQL, MySQL, SQL Server, and Oracle. Through this training, you’ll be able to work with any of these databases since the queries formation processes are similar.
Other topics you’ll cover include selecting columns, filtering data in rows, as well as using aggregate functions to summarize data, so you can derive useful insights.
4. Introduction to Power BI
Data science and data visualization go hand in hand. This is because while you may understand what you are doing, you need to present this data into a more layman friendly form, in graphs and charts, for the less technical to comprehend.
Microsoft Power BI software is one of the most popular data visualization tools, besides Tableau, that you should consider learning for data analysis projects.
In this Power BI course on Datacamp you’ll get a total overview of Power BI by exploring the various ways you can use it to build impactful dashboards and reports.
So even if you are completely new to data analysis, this course takes you from zero to pro in the ins and outs of Power BI by leveraging practical, hands-on exercises that make the learning process more fun.
Other skills you’ll pick up include how to load and transform data, the importance of data models, as well as creating interactive reports.
5. Data Science for Everyone
Now we are getting into more meaty courses.
I think till today enthusiasts still struggle to find a proper way to define data science. This is because it is so vast and covers a ton of technologies that just a couple of words may not suffice.
That being said, this is the best Datacamp course in 2023 that provides you with a proper introduction to data science, without delving into code.
In this course, you’ll learn what data science primarily is about. You’ll explore some of the reasons why it is such a popular career, including why it was ranked the sexiest job by the Harvard Business Review.
It is basically a theoretical course that takes you through the different data scientist roles, and provides you with an introduction to A/B testing, time series analysis, and machine learning use cases.
At the end you’ll know how data science professionals derive knowledge and business insights from raw business data.
6. Data Analysis in Spreadsheets
Spreadsheets are key to data analysis.
They enable you to sort out data, group as well as filter them based on set criteria that makes visualization easy. That is not to mention more advanced spreadsheet functions that perform magic on structured data.
In this Datacamp course, you’ll take a deep dive into the core functionality of Google Sheets, one of the most popular spreadsheet programs beside Microsoft Excel.
Through this course you’ll cover the complete array of Google Sheets functions, including the most popular ones like SUM, AVERAGE, and VLOOKUP.
Once you know how to use them, you’ll implement them in some practice data analysis exercises where you’ll work with school grades, and examine company performance statistics.
Other hands-on exercises involve tracking monthly sales, as well as looking at some real geographical information about countries across the globe. At the end you’ll be able to solve complex problems simply by leveraging different spreadsheet functions.
7. Analyzing Data in Tableau
If you want to become a data analyst worth his salt, you should master as many data analysis and visualizations tools as possible.
This way you’ll be able to work with any tool thrown at you, which means being more efficient and effective at your job.
In this popular Datacamp training, you’ll learn what it takes to push your Tableau skills a notch higher by exploring some of the most advanced data analysis and visualization features that the Tableau software provides.
You’ll learn how to create detailed map visualizations, as well as configure data and time fields to show trends over time.
What’s more, you’ll be able to take your skills a little further by completing a customer analysis case study. Here you’ll look at creating bins, customizing filters and interactions, as well as applying quick table calculations.
Other skills you’ll pick up include slicing and dicing data, skills that’ll make you ready for the Tableau certification exam.
8. Data Processing in Shell
The command line is one of the tools you’d least expect to talk about when it comes to performing serious data analysis operations on big data.
However, the Shell command line can also be used to run commands for downloading, processing and actually transforming datasets, as well as running some machine learning pipelines.
In this course you’ll take a step away from GUI tools, and learn how to use the command line to perform data analysis operations, hence becoming more productive.
You’ll focus on the practical and powerful data specific command line skills for downloading, processing, cleaning, and transforming publicly available Spotify data. You’ll also get to perform some advanced command line based SQL operations.
At the end you’ll have mastered the techniques for combining the powers of the command line and Python programming to build a data pipeline for automating a predictive data model.
Other skills you’ll pick include using the CSVkit library, as well as installing dependencies.
9. Data Analysis in Excel
Like I mentioned before, Microsoft Excel and Google Sheets are the two most popular spreadsheet tools among data analysts.
While you might only be aware of their rudimentary features used for summing and presenting tabular data, these tools are equipped with more advanced features that are key to data analysis and visualization.
Here is one of the best Datacamp courses in 2023 that will teach you how to use Microsoft Excel to transform huge amounts of data into information that you can derive useful insights from, for data-driven business decision making.
You’ll explore different time saving keyboard shortcuts to work with different data sets like text, times and dates so you can build impressive conditional aggregations.
Some of the new Excel functions that you’ll cover include CONCATENATE, VLOOKUP, and AVERAGEIF.
What’s more, you’ll get to work with real-world Kickstarter projects data as you put your new Excels skills to work, analyzing what makes a project successful in the face of scarce resources.
10. Introduction to Git
Git and GitHub are the most popular tools for storing software source code, as well as version controlling applications. This way you can never completely lose source code, besides making it easy to rollback to previous versions if a new update breaks code.
Even data scientists need to version control their code because it is very common for bugs to pop in and not immediately know what is not happening.
In this Datacamp course you’ll learn how you can keep track of what you are doing, undo any changes you don’t want to keep, as well as collaborate with other engineers so you can scale your development team.
You’ll explore the main features and commands in Git, a modern version control tool popular among software engineers and data scientists.
Some of the topics you’ll cover include the basic version control workflows, repository creation and management, as well as working with branches and collaborating with remote teams.
11. Introduction to Scala
If you’ve been reading any data science content lately then you probably have already heard of Scala programming.
Let’s say that today, Python, R and Scala are the most popular programming languages for data science that you should learn if you are a complete beginner.
In this top Datacamp course, you’ll get a proper introduction into the foundational concepts of Scala programming. You’ll also explore the reasons why big tech companies like Netflix and Airbnb have chosen to leverage Scala for their data engineering infrastructure.
You’ll begin by covering the basics of Scala where you’ll look at the syntax and style, while focusing on the most important data science features of Scala.
What’s more, you’ll learn through hands-on practice where you’ll write code for an actual application that emulates the popular card game Twenty-One.
In fact, you’ll kill two birds with one stone as you’ll master both functional programming and object oriented programming at the same time.
12. Introduction to Statistics in Python
Probability and statistics is at the core of most data science and machine learning models that big data analysis tools run on.
It is therefore critical that you get your statistics and probability skills up to speed if you want to better understand how various machine learning and computer vision algorithms work.
This is another one of the best courses on Datacamp for learning how to collect, analyze and derive insights from data.
With these skills you’ll be able to bring the future into focus, while inferring and answering a ton of questions beforehand.
Some of the business questions data scientists seek to answer include the likelihood of someone purchasing a product, the number of calls a support team is likely to receive, as well as the number of shoe sizes to manufacture that’ll fit 95% of the population.
At the end you’ll use Python to conduct a well designed case study, and draw your own insightful conclusions.
13. Machine Learning for Everyone
Machine learning and computer vision are at the core of most artificial intelligence powered applications.
So before you get your data science cog wheels spinning, you should first acquire a proper understanding of machine learning principles because you’ll encounter this term quite often during your studies.
In this rather theoretical Datacamp training, you’ll get to master some of the most elusive concepts of data science and machine learning. The concepts that most people avoid trying to explain, for fear of misplacing a word or two in their definitions.
In fact, you’ll get past the jargon, often throw left, right and center, and explore the various ways this revolutionary technology forms the backbone of self-driving cars, and highly converting product recommendations on Amazon.
At the end you’ll know the difference between artificial intelligence and machine learning, what machine learning is really capable of thus preparing you for a career in this influential field.
14. Data Manipulation with pandas
The great thing about using Python for data science is that you’ll find a library or package for almost any task you’d like to run.
Python Pandas is one of the most popular data science packages, based on the Python language, that you can use for data analysis.
This is the best Datacamp course in 2023 for learning how to analyze and manipulate big datasets using the Pandas library.
You’ll start off by exploring how to manipulate DataFrames, while extracting, filtering, and transforming real world datasets for analysis and visualization, so that you can finally extract some useful insights. I consider this a great approach to mastering the core data science concepts for junior data scientists.
What’s more, you’ll handle a hands-on project where you’ll use real sales figures and temperature time series data from Walmart. Here, you’ll get to master the best techniques importing, cleaning, and creating data visualizations using Pandas.
15. Introduction to the Tidyverse
Tidyverse is an all capable and popular collection of data science tools that are designed and built using the R programming language.
Since all packages that constitute Tidyverse share the same underlying design philosophy, grammar and data structures, mastering this toolset will make your data science projects more fun and easier to run.
In this Tidyverse course on Datacamp you’ll get an introduction to R programming, with a particular focus on the Tidyverse set of tools.
Once you cover R basics, you’ll explore the intertwined processes of data manipulation and visualization with the help of tools like dplyr and ggplot2. Here, you’ll master the techniques for filtering, sorting, and summarizing data.
The data visualization aspect involves turning processed data into informative and consumable charts and graphs using the amazing ggplot2 package.
I find it a great course if you are new to R but would like an introductory R course with particular focus on data analysis.
16. Introduction to Data Visualization with Matplotlib
Being able to create great data visualizations is at the core of launching a successful career in data science today.
This is because the objective of data analysis is to be able to derive useful insights that can form the basis of data driven decision making, and it is through a very informative data presentation that we can make inferences about behaviors and trends.
Matplotlib is one of the best Python libraries for creating data visualizations.
In fact, this is one of the best Datacamp courses that will teach you how to use Matplotlib to plot data so that you can expose the underlying patterns and insights.
Through this online training, you’ll acquire fundamental knowledge in the core Matplotlib building blocks for creating rich data visualizations of a vast collection of datasets, touching different industries.
You’ll also be able to customize, automate, and share the data visualizations and presentations that you create with other consumers of the data.
17. Intermediate Python for Finance
Is coding necessary for finance professionals?
I’d say that today, you’d be hard pressed to find an industry where there are no tasks that can be automated by coding some scripts, probably in Python.
Finance is one of the most calculation intensive industries. It would benefit to have some coding skills under your belt to automate certain repetitive tasks.
In this Datacamp training you’ll learn how to automate tasks like risk calculation, market health mapping, and stock price trends visualization, using the Python language.
It is one of the best coding for finance courses, where you’ll start with the basics of Python, then proceed to more intermediate features like using data structures and control statements to collect and manipulate financial data.
What’s more, there is a practical hands-on project where you’ll work with real world data from the Federal Reserve Bank. Here, you’ll use the Pandas library to explore national economic trends, so that you can understand key investment strategies that bring great returns on investments.
18. Analyzing Marketing Campaigns with Pandas
Data analytics and visualization has had one of its most successful applications in sales and marketing campaigns.
It has made it possible to derive very critical insights from data that just a couple of years ago didn’t mean much, especially when it comes to unstructured customer data that traditional applications cannot analyze.
In this online course on Datacamp, you’ll learn how to translate common business questions into measurable outcomes using various data analytics techniques and tools like Python Pandas.
Some of the basic questions you’ll be able to answer include gauging marketing campaign performance, identifying the channel that’s referring the most subscribers, as well as establishing why certain channels have suboptimal performance.
Interestingly, you’ll be using a fake marketing dataset derived from an online subscription business database.
Finally, you’ll have mastered the Pandas fundamentals to level up in your marketing job, as well as get a handle of what role a data scientist will play in your business.
19. Cleaning Data in Python
In software engineering we have a damn old saying, “garbage in, garbage out”.
Well, this applies to data science as well. If you want your data models to give you accurate output and predictions, then the data that you feed them must be of good quality. The first step in making data of good quality is cleaning the data.
This is the best Datacamp course for learning the top techniques for cleaning data for your data science projects.
Here, you’ll explore the processes involved in identifying, diagnosing, and treating a variety of data cleaning problems in Python. You’ll start with simple techniques, then advance to more involving methods of data cleaning.
Some of the most common tasks you’ll seek to undertake with your data cleaning techniques include dealing with improper data types, checking whether your data falls in the correct ranges, handling missing data that’s critical to the analysis process, as well as performing record linkage.
20. Data Engineering for Everyone
If you find the roles of data engineers and data scientists confusing, then this course will help you dispel some of that confusion.
Principally, you’ll get to establish how a data engineer helps establish the data scientist’s role by laying the groundwork that makes any data science possible.
You’ll begin by exploring what the data engineer’s responsibilities are. This way you’ll be able to differentiate them from those of a data scientist, while establishing how they help facilitate the flow of business data in your enterprise.
Besides, you’ll work through a practical, hands-on exercise involving a fictional music streaming company. The objective is to establish how their data engineers collect, clean, and catalog their business data.
At the end of this Datacamp course, you’ll know what your data engineers actually do, so that you are more comfortable having a conversation with any of them.
It’s the foundation you need to start your own data engineering journey.
21. Case Study: Exploratory Data Analysis in R
One of the best ways to put your data science skills to use is by combing through a case study that gives you the opportunity to shine.
I like case studies because they give you the opportunity to put the skills, techniques and tools you’ve been learning to some real test, while working with actual datasets from companies you can actually relate with.
In this course, you’ll use data manipulation and visualization tools, like dplyr and ggplot2, to explore the historical voting trends of the United Nations General Assembly.
You’ll use data analysis to establish the differences in voting tendencies between different countries over time.
It is one of the best Datacamp courses to take in 2023 that will provide you with hands-on practice using dplyr and ggplot2 packages.
Other skills you’ll pick up include using the broom package for tidying up the output of your data models, while taking a project from start to finish.
22. Case Study: Analyzing Customer Churn in Power BI
Like I mentioned before, Microsoft Power BI is one of the best business intelligence tools for analyzing and visualizing business data.
This particular case study gives you the opportunity to let your Power BI skills shine by using business data to analyze the customer churn and burn for an enterprise.
In this Datacamp case study, you’ll work with a dataset from a fictitious telecom company called Databel, with the objective of analyzing and establishing their customer churn rates.
Keeping customer churn rates low is a priority for any subscription based business.
By working through this case study, you’ll get to establish what the actual churn rate is, figure out why customers are churning out of the company’s services that fast, and come up with possible solutions for reducing this churn and burn.
Finally, you’ll nicely put this together in a dashboard, ordered by user stories, and present it to stakeholders who can act on your findings.
23. Case Study: Analyzing Customer Churn in Tableau
Just like the previous case study, this is another case of a churn rate analysis but using Tableau, instead of Power BI this time.
It is another one of the top Datacamp courses to take if you already have some intermediate Tableau skills that you’d like to put to work. Remember, a case study focuses on application of the skills, not acquisition.
Here, you’ll analyze a dataset from a telecom company in order to establish their churn rates.
Your objective is to find out what their churn rates actually are. In addition to that, you’ll seek to figure out why their customers churn at that particular rate, so that you can come up with actionable insights on how to curb the churn.
You’ll use the Tableau software to create calculated fields and visualizations that will enable you to expose the underlying patterns, making them obvious to the naked eye.
By leveraging user stories, you’ll be able to make your Tableau skills really shine.
24. Data-Driven Decision Making for Business
The last case study in this list of Datacamp courses still leans on using data science concepts as the basis of data driven decision making for enterprises.
Here, you’ll focus on acquiring the mastery in applying practical data models and frameworks to making business decisions.
In fact, the course starts by taking you through the basics of data-driven decision making. You’ll then proceed to explore how you can apply these skills to real world use cases in finance, marketing and operations management.
Some of the frameworks you’ll learn in the process include supply and demand, risk and rewards, as well as cost and benefits frameworks.
Finally, you’ll be able to efficiently read and analyze the data that your company collects. This is actually a critical skill that should be picked up, at least past the beginner level, by staff in every role in your organization.
It’ll make it very easy to uncover new insights and glaring opportunities.
25. Cloud Computing for Everyone
I could not end this list of Datacamp courses without mentioning something on cloud computing technologies.
Cloud computing is a revolutionary technology whose use is sweeping across various internet based, as well as some offline companies, for data storage and processing.
In this cloud computing course, you’ll start by looking into what cloud computing actually is in the first place, then proceed to establish why it has become such a buzz, that enterprises of all sizes are rushing to adopt it.
Some of the terminology you’ll pick up include scalability, latency and high availability.
Besides, some of the advantages of cloud computing that you’ll establish by taking this online class include the ease of remote collaboration, unlimited access to immense hardware processing power, as well as disaster recovery plans you can count on.
Finally, you’ll be able to explain how cloud technologies like Google Cloud, Amazon AWS, and Microsoft Azure increase productivity, while keeping costs down.
Related:
Best Codecademy Courses
Best Udemy Courses
Conclusion
Datacamp is the best online platform for picking up skills in data analysis, predictive analytics and data visualization.
Even so, there still comes the overwhelm caused by the huge collection of courses.
I hope this review of the best Datacamp courses and certifications to take in 2023 has provided you with some guidance on the top courses for learning certain skills.
If you are still at the beginning stages of a career in data science, the Introduction to Python for Data Science course is what you are looking for. Here you’ll get a soft intro to Python and data science at the same time.
However, if you already have the basics nailed down and you want to get down to some real analytics work, the Analyzing Data in Tableau course will provide the excitement. Together with Power BI they are the best data visualization tools to master.
Have you taken any of these courses on Datacamp before?
Please share your thoughts below.
