2023’s Top DataCamp Courses

Courses at DataCamp – Overview

The demand for data scientists is rising and will continue to rise. The goal of DataCamp is to make data literacy accessible to anyone. Here is where you should start if you want to learn more about the subject while working.

Skill tracks and individual courses are two of the learning models offered by DataCamp. A course is narrowly focused on a single topic, but a skill track explores the topic in depth and contains numerous DataCamp courses. An introduction course might be the first step for a newbie, after which they can progress to the skill track for more in-depth understanding.

Learning – The learning process consists of interactive courses with tests to assess learner’s progress. Students can also practice with daily challenges and apply their knowledge to create real-world projects. There is also DataCamp Community, which offers in-depth tutorials, cheat sheets, podcasts, and free DataCamp courses in DataScience.

Pricing – You can access the first chapter of all DataCamp courses for free. To access the full course catalog, challenges and live coding environments, you can sign-up to the Standard plan for $25/month/annually. For $33/month/annually, Premium additionally offers 80+ real-world projects, Tableau, Power BI, and Oracle content, and priority support.

  • Introduction to Python Python is one of the most popular programming languages for data science. The DataCamp Python course (visit website) is an excellent place to learn its principles as a beginner and create a versatile foundation for various career and skill tracks in technology. It starts with a chapter on Python Basics like creating a Python script, variables, and data types. The second chapter covers lists, the most popular data structure in Python. Students learn to store, access, and manipulate data in lists.  How to use functions, packages, and methods to structure and reduce Python code are essential follow-ups to complete the basics. Of course, learning how to import and use popular data science packages in Python such as NumPy will be covered too. After the course, you can continue with skill tracks to learn more about the subject. This course is a part of Data Science for Everyone, Machine Learning for Everyone, Data Scientist, and Python Fundamentals. The latter builds upon the introduction module.Overall, this is one of the best DataCamp courses to get started on the platform.
  • Instructor: Hugo Bowne-Anderson |
  •  Duration: 4 hours | Videos: 11 | Exercises: 57 Pricing: Standard Plan for $25/month. Premium: $35/month
  • Info: Visit website. Get a discount on all plans. Free trial.
  • DataCamp’s introduction to R (visit website) discusses various concepts in the open-source language R. Data Science relies heavily on statistical methods, and R is the ideal tool for implementing statistical operations and visualizing results. There are six chapters. It starts with an introduction to R basics like assigning variables and using the console as a calculator. The second and third chapters discuss vectors and matrices in R. The fourth chapter discusses the importance of factors in data analysis. In the last two, students learn to work with data structures such as data frames and lists. If you’re considering a career in data science, then R is an excellent language to master. It’s also part of data analyst, data scientist, and the DataCamp R programming skill tracks.
  • Instructor: Jonathan Cornelissen |
  • Duration: 4 hours | Videos: 0 | Exercises: 62 Pricing: Standard Plan for $25/month. Premium: $35/month
  • Info: Visit website. Get a discount on all plans. Free trial.

Data Science for Everyone

  • When a data science course jumps right into coding, it’s natural to be alarmed. If that happened to you, then Data Science for Everyone (visit website) is a great choice. This DataCamp course introduces DS to an absolute beginner, with no coding involved. The course begins with an introduction to data science. This covers the workflow in data science, how data science is implemented in real-world problems and various roles in the data science field. It will also talk about data collection and storage. The following modules cover the preparation, exploration, and visualization of data. It’s the most important part of data analysis and most data scientists spend 80% of the time cleaning and manipulating data, while only 20% of time analyzing it. This is one of the best DataCamp courses to get started with DataScience. It includes a chapter on experimentation and prediction and covers A/B testing and series forecasting. 
  • Instructor: Sara Billen |
  •  Duration: 4 hours | Videos: 15 | Exercises: 48 Pricing: Standard Plan for $25/month. Premium: $35/month 
  • Info: Visit website. Get a discount on all plans. Free trial.

Introduction to SQL

  • If you’re considering a career as a DBA (database administrator) or data scientist, then SQL is the basic requirement. The structured query language (SQL) is used to communicate with the database. This Datacamp SQL course (visit website) will push you in the right direction. You will start on how to start working with a relational database. That includes database structure, lingo, and beginning data analysis with simple commands like Select. The second chapter talks about filtering rows using comparison operators and matching patterns in text. Aggregate functions to summarize data for insights are discussed in the next chapter and arithmetics and aliases in SQL. This DataCamp course concludes with a chapter on sorting and grouping results in an RDB. 
  • Instructor: Nick Carchedi |
  •  Duration: 4 hours | Videos: 1 | Exercises: 41 Pricing: Standard $25/month. Premium $35/month
  • Info: Visit website. Get a discount on all plans. Free trial.

Data Engineering for Everyone

  • Data scientists are pretty common, but data engineers are not! This DataCamp course (visit website) explores the difference between a data scientist and a data engineer and builds a foundation to begin your data engineer journey. The course is pretty short and consists of only three chapters covered within two hours. The first chapter gives an introduction to data engineering and introduces learners to their first data pipeline. The second chapter explores data storage and how data engineers manage data lakes and data warehouses. The last lesson is about data movements and processing. It explains various techniques used by data engineers and an introduction to parallel computing and cloud computing. 
  • Instructor: Hadrien Lacroix |
  •  Duration: 2 hours | Videos: 11 | Exercises: 32 Pricing: Standard $25/month. Premium $35/month
  • Info: Visit website. Get a discount on all plans. Free trial.

Data Science for Business

  • Data science is important for every organization, but the question is how and for what. This is one of a couple of Datacamp courses that explore that question and teaches you how to use data science for business (visit website). At first, there is a brief introduction to data science which proceeds to data collection and storage in the following lessons. Building upon this, you will learn about the analysis and visualization of data through dashboards, A/B testing, and Ad hoc data requests. The last module covers machine learning, the buzziest topic in data science. It covers supervised and unsupervised learning and clustering and concludes a chapter with topics like time series prediction, NLP, deep learning, and explainable AI. 
  • Instructor: Mari Nazary | 
  • Duration: 4 hours | Videos: 14 | Exercises: 51 Pricing: Standard $25/month. Premium $35/month 
  • Info: Visit website. Get a discount on all plans. Free trial.

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