Category: R

Get Hired Faster with a DataCamp Certification

Turn online learning into career-advancing Certifications on DataCamp.

Are you looking to kickstart your data career without breaking the bank?

This article is for you.

DataCamp is a world-leading data and AI education platform. It’s known for its interactive learning and extensive collaboration with industry experts to prepare learners for the data-driven workforce.

What are DataCamp Certifications?

Ranked the #1 data certification by Forbes, DataCamp Certifications offer a direct path for turning online learning into a successful data career.

Positioned as the final piece of their tailored learning paths, Certifications sit at the end of their ‘Career Tracks’. In many cases, you start from scratch and build your way up to gaining an industry-leading certification in your chosen field.

Or, you can dive straight into a Certification if you have pre-existing knowledge. There’s no blocker on which certification you can take or how many you are allowed to complete.

If you’re starting, pivoting, or accelerating your career, Certifications are a fast route into in-demand data roles. No longer are these roles kept behind University Degrees and expensive qualifications, you can learn and prove job-ready skills all on DataCamp.

What Certifications are on offer?

DataCamp Certifications have been created in collaboration with industry experts and hiring managers. They reflect the most sought-after roles and the rigorous exam process ensures all certified learners are job-ready for that specific role.

Here’s a peek at what DataCamp offers. For the full list, head to their Certification Hub.

Career Certifications

Designed to show you’re 100% job-ready, career certifications test the skills you need to get your first data role.

  • Data Analyst
    Showcase your ability to answer business-critical questions, effectively visualize data, and communicate insights.

  • Data Scientist
    Demonstrate that you can collect, analyze, and interpret large amounts of data using machine learning and AI.

  • Data Engineer
    Show you can make data usable and valuable for others by collecting, processing, and publishing large datasets.

Technology Certifications

Aimed at individuals working with data in any role, our technology certifications show that you can use specific technologies to work with data.

  • SQL Associate Certification
    Demonstrate that you are capable of using SQL to extract appropriate data from a database, and use it to answer common data questions.

  • Exam PL-300: Microsoft Power BI Data Analyst
    Created in partnership with Microsoft, the PL-300 exam tests all core Power BI skills. You get a 50% discount on the official certification through Microsoft and DataCamp.

Fundamentals Certification

Perfect if you’re just getting started and want to boost your CV. Fundamentals Certifications demonstrate you have the core skills to make data-driven decisions and enhance your productivity with AI.

  • AI Fundamentals
    For individuals new to AI or seeking to enhance their knowledge. It covers essential AI concepts including the difference between different AI domains and understanding Generative AI ethics.

  • Data Literacy
    A great place to start if you’re new to data! Show you know about different types of data and common analytic techniques. You will also demonstrate you can interpret a visualization and obtain vital information.

How do I start?

Anyone with a free DataCamp account can access the first chapter of each course. So, before spending anything, you can test the platform and see if it’s the right fit for you.

After that, DataCamp offers a single Premium subscription which offers unlimited access to all learning materials; including all courses, certifications, projects, and more.


All certifications are graded in partnership with industry experts through a series of timed and practical tests. More advanced certifications offer a window to complete all tasks, while fundamental options can be taken there and then.

Unsure about your level? No problem. Take a five-minute self-assessment to determine the best fit and learning plan for you.

Once you’re certified, you’ll get access to DataCamp’s exclusive certification community. You’ll be able to connect with other certified professionals and explore content curated just for you by our community team.

Your DataCamp subscription can be paid monthly or yearly to fit all budgets.

Build skills. Get hired.
Discover more.

Free Report: DataCamp’s The State of Data & AI Literacy Report 2024

Free Report: DataCamp’s The State of Data & AI Literacy Report 2024

DataCamp has commissioned a free report surveying 550+ business leaders on the rising demand for data and AI skills. Download now to uncover which skills employers are hiring for in the era of generative AI.

Keep reading for a peek at the report’s key findings or download it for free now.

Demand for data and AI skills is rising. What skills should you prioritize to make you more employable?

DataCamp’s report explores the skills landscape for some of the world’s leading organizations, focusing on the skills leaders value most and their current skills gaps.

Spoiler: data and AI rank high across the board.

Specifically, 86% of leaders believe data literacy is now vital for day-to-day tasks and 72% are prepared to pay a salary premium for employees with data literacy skills.

Going deeper, DataCamp sought to understand which specific data and AI skills leaders are looking for in their teams, uncovering:

  • 84% consider data-driven decision-making a critical skill
  • 83% look for employees who can interpret data visualizations and dashboards
  • 80% value data analysis and manipulation

For AI skills:

    • 70% consider the basic understanding of AI concepts the most crucial AI skill
    • 69% emphasize AI ethics and responsible AI practices as a vital part of their team function
    • 65% recognize the application of AI in a business context as crucial

    And much more. Download the report for the complete insights.

    How are leaders building data and AI skills? Five lessons leaders are using to create best-in-class teams

    Leaders with mature programs report a notable increase in benefits across several areas: decision-making efficiency jumps to 90%, innovation to 87%, and employee retention to 81%.

    Moreover, drawing on first-hand experiences from DataCamp’s B2B clients like Colgate-Palmolive, Rolls Royce, and Specsavers—dive into the best practices for effectively implementing successful data and AI upskilling and reskilling programs:

    • Expand existing programs to include AI literacy: Broaden data upskilling initiatives to encompass AI literacy as an integral extension of data skills

    • Widen the reach of upskilling initiatives: Extend the scope of training to include non-technical roles, enhancing organizational-wide AI literacy

    • Focus on interactivity and personalization: Center learning programs around interactive and personalized training for effective skill development

    • Leverage AI as a force multiplier: Utilize AI to enhance and accelerate the application of data skills across the organization

    • Proactive change management: Emphasize positive reinforcement and change management to address workforce concerns about new technologies

    For more detailed insights and recommendations, read the full report.

    Beyond the workplace: Data and AI literacy as social safeguards

    The report also explores how data and AI literacy serve as critical societal safeguards against humanity’s most pressing challenges—including online misinformation, bias from AI systems, and job automation.

    What DataCamp found for each challenge:

    • Online misinformation and disinformation: 73% acknowledge that AI literacy is pivotal in mitigating online misinformation and disinformation

    • Bias from AI systems: 75% agree every employee should be trained in ethical AI practices to prevent biases that can fuel social injustices and distort data-driven decisions

    • Job automation: 57% suggest that well-trained individuals are less likely to be affected by automation. Additionally, 75% believe that nations and organizations have a responsibility to prepare their workforce for these changes.

    Download the Full Free Report

    This article touches on a fraction of the findings. 

    Download the full report to learn more about the present and future of data and AI literacy and how they might impact your career and organization.

    {cryptoQuotes}: Open access to cryptocurrency market data in R (Update)

    The {cryptoQuotes}-package have been updated to version 1.3.0. With this update comes many new features,  and breaking changes. Prior to version 1.3.0 the package were using camelCase (See for example this post), with no particular style guide. The package now uses the tidyverse style guide which, in return, have deprecated a few core functions.

    Note: Only the styling is affected, the returned market data is still xts/zoo-objects
    Of the many new features and enhancements includes dark and light themed charting, and  a wide array of new sentiment indicators. The full documentation can be found on pkgdown.

    In this blog post the new charting features will be showcased using hourly Bitcoin OHLC-V and long-short ratios from the last two days (From writing this draft).

    Cryptocurrency market data in R

    # 0) load library
library(cryptoQuotes)
    To extract the Bitcoin OHLC-V,  the get_quote()-function [previously getQuote()]  is used as  shown below,

    # 1) extract last two
# days of Bitcoin on the
# hourly chart
tail(
  BTC <- get_quote(
    ticker   = "BTCUSDT",
    source   = "binance",
    interval = "1h",
    from     = Sys.Date() - 2
  )
)
#>                        open    high     low   close    volume
#> 2024-06-05 02:00:00 70580.0 70954.1 70462.8 70820.1  7593.081
#> 2024-06-05 03:00:00 70820.2 71389.8 70685.9 71020.7 11466.934
#> 2024-06-05 04:00:00 71020.7 71216.0 70700.0 70892.1  7824.993
#> 2024-06-05 05:00:00 70892.2 71057.0 70819.1 70994.0  5420.481
#> 2024-06-05 06:00:00 70994.0 71327.9 70875.9 71220.2  7955.595
#> 2024-06-05 07:00:00 71220.2 71245.0 70922.0 70988.8  3500.795
    The long-short ratios on Bitcoin in the same hourly interval is retrieved using the get_lsratio()-function [previously getLSRatio()] as shown below,

    # 2) extract last two days
# of long-short ratio on
# Bitcoin
tail(
  BTC_LS <- get_lsratio(
    ticker   = "BTCUSDT",
    source   = "binance",
    interval = "1h",
    from     = Sys.Date() - 2
  )
)
#>                       long  short  ls_ratio
#> 2024-06-05 02:00:00 0.4925 0.5075 0.9704433
#> 2024-06-05 03:00:00 0.4938 0.5062 0.9755038
#> 2024-06-05 04:00:00 0.4942 0.5058 0.9770660
#> 2024-06-05 05:00:00 0.4901 0.5099 0.9611689
#> 2024-06-05 06:00:00 0.4884 0.5116 0.9546521
#> 2024-06-05 07:00:00 0.4823 0.5177 0.9316206
    Prior to version 1.3.0 all charting with indicators were done with the magrittr-pipe operator, both internally and externally. This came with a overhead on both efficiency and readability (Opinionated, I know). The charting has been reworked in terms of layout and syntax.

    Below is an example of a dark-themed chart with the long-short ratio alongside simple moving averages, bollinger bands and volume indicators,

    # 3) dark-themed
# chart
chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    bollinger_bands(),
    sma(n = 7),
    sma(n = 14)

  ),
  sub = list(
    volume(),
    lsr(ratio = BTC_LS)
  )
)

    The light-themed chart have been reworked, and have received some extra love, such that its different from the default colors provided by the {plotly}-package,

    # 4) light-themed
# chart
chart(
  ticker = BTC,
  main   = kline(),
  indicator = list(
    bollinger_bands(),
    sma(n = 7),
    sma(n = 14)
  ),
  sub = list(
    volume(),
    lsr(ratio = BTC_LS)
  ),
  options = list(
    dark = FALSE
  )
)

    About the {cryptoQuotes}-package

    The {cryptoQuotes}-package is a high-level API-client that interacts with public market data endpoints from major cryptocurrency exchanges using the {curl}-package.

    The endpoints, which are publicly accessible and maintained by the exchanges themselves, ensure a consistent and reliable access to high-quality cryptocurrency market data with R.

    Installing {cryptoQuotes}
    The {cryptoQuotes}-package can be installed via CRAN,

    # installing {cryptoQuotes}
install.packages(
  pkgs ="cryptoQuotes",
  dependencies = TRUE
)

    Created on 2024-06-05 with reprex v2.1.0

    Meta-Analysis in R workshop

    Join our workshop on Meta-Analysis in R, which is a part of our workshops for Ukraine series! 

    Here’s some more info: 

    Title: Meta-Analysis in R

    Date: Thursday, July 11th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone) 

    Speaker: Matthew B. Jané is a graduate student in quantitative psychology at the University of Connecticut. His interests involve data visualization and statistical methods for meta-analysis and psychometric measurement. He is affiliated with the Systematic Health Action Research Program where he is advised by Dr. Blair T. Johnson. 

    Description: In this workshop, we will learn how to conduct meta-analysis in R using real data sets. We will first discuss how effect sizes such as standardized mean differences, correlations, and odds ratios are calculated. Then we will discuss three types of meta-analytic models (i.e., common, fixed, and random effects models) and how we can fit each model in R. Finally, we will visualize how study characteristics can moderate effect sizes with the help of meta-regression.

    Minimal registration fee: 20 euro (or 20 USD or 800 UAH)


    How can I register?



    • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

    • Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

    If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.


    How can I sponsor a student?


    • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

    • Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.

    If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).


    You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.

    Looking forward to seeing you during the workshop!

    Polytomous Latent Class Analysis and Regression in R workshop

    Join our workshop on Polytomous Latent Class Analysis and Regression in R which is a part of our workshops for Ukraine series! 

    Here’s some more info: 

    Title: Polytomous Latent Class Analysis and Regression in R

    Date: Wednesday, July 3rd, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone)

    Speaker: Lana Bojanić is a research associate and PhD candidate at the University of Manchester. With over 7 years of experience using R, she is also a co-founder of the R user group at the University of Manchester and R Ladies Zagreb, Croatia. Lana is passionate about introducing people to R and supporting them during their transition to full-time R users.

    Description: Polytomous (multi-category) data is common in many fields that utilise surveys, tests or- assessments. This workshop will deal with latent class analysis and latent class regression analysis of this data type, using PoLCA package. Furthermore, we will cover the necessary data preparation for this analysis, specifying the model, and calculating/extracting fit values. Finally, we will look into different ways of plotting results for this analysis.

    Minimal registration fee: 20 euro (or 20 USD or 800 UAH)



    How can I register?



    • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

    • Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

    If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.


    How can I sponsor a student?


    • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

    • Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.


    If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).



    You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.


    Looking forward to seeing you during the workshop!

    Effective Visual Communication with R workshop

    Join our workshop on Effective Visual Communication with R, which is a part of our workshops for Ukraine series! 


    Here’s some more info: 

    Title: Effective Visual Communication with R

    Date: Thursday, June 20th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone) 

    Speaker: Claus Wilke is a data scientist and computational biologist at The University of Texas at Austin. He is known for his work on popular R packages for data visualization, such as cowplot, ggridges, and ggtext, as well as his contributions to the package ggplot2. He is also the author of the book Fundamentals of Data Visualization, published in 2019, which provides a concise introduction to effectively visualizing many different types of data sets.

    Description: In the first half of this workshop, Wilke will provide a high-level perspective on how to make good visualizations and how to use them effectively to communicate and reason about data. The second half will be more hands-on and will address how to use R to make interactive plots, deal with overplotting, and make compound figures.

    Minimal registration fee: 20 euro (or 20 USD or 800 UAH)


    How can I register?


    • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)
    • Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

    If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.


    How can I sponsor a student?

    • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)
    • Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.


    If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).


    You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.

    Looking forward to seeing you during the workshop!

    Free DataCamp Online Conference: Radar: AI Edition, June 26–27, 2024

    ChatGPT was only the beginning. Generative AI is now revolutionizing every industry. 

    As the race to adopting AI tools intensifies, the decisions we make today about AI will likely shape our success for decades to come.

    To learn how the world’s data and AI leaders are adapting to this new era, join DataCamp on June 26–27 for RADAR: AI—a two-day digital event exploring how businesses and individuals can unlock their full potential with AI.

    Register Now

    From scaling AI within your organization and driving innovation to navigating the evolving job market, uncover practical steps to implement in your career or organization to maximize the power of generative AI.

    A star-studded agenda:


    Including voices from GitHub, Dropbox, PwC, Hugging Face, Accenture, and many more, unpack how AI is evolving and how you can take advantage.


    A peak at what to you can expect:

    June 27, 2024 (all times EDT):


    9:00–9:45
    Welcome to RADAR!
    Jonathan Cornelissen, Co-Founder & CEO, DataCamp


    9:50–10:35

    Generative AI in Practice: 100+ Amazing Ways Generative AI is Changing Business and Society 

    Bernard Marr, World-renowned Futurist, AI Advisor, and Author of “Generative AI in Practice”, Bernard Marr & Co


    10:50–11:35 

    From Learning to Earning: Navigating the AI Job Landscape

    Sadie St Lawrence, Founder & CEO at Women in Data, and Megan Finck,

    Global Head of Talent Acquisition—Engineering, IT and Data Analytics, Boeing


    11:40–12:25

    Generative AI: Trends, Impact, and Practical Applications for 2024

    Principal, Insight Partners, and Sandhya Venkatachalam, Partner, Axiom Partners


    12:40–1:25 

    The High Cost of AI Hype

    Eric Siegel, Founder of Machine Learning Week, Prediction Impact


    1:30–2:15
    Building Tomorrow’s Workforce, Today: Scaling Internal AI Academies
    Mike Baylor, CDAO, Lockheed Martin, Carolann Diskin, Senior Technical Program Manager, Dropbox, Matthew Graviss, and CDAIO, U.S. Department of State


    2:20–3:05

    Scaling Data Quality in the Age of Generative AI

    Barr Moses, CEO, Monte Carlo Data, Prukalpa Sankar, Co-founder, Atlan, and George Fraser CEO, Fivetran


    June 27, 2024


    9:00–9:45
    Building Trust in AI: Scaling Responsible AI Within Your Organization

    Haniyeh Mahmoudian, Chief AI Ethicist at Datarobot, Eske Montoya Martinez van Egerschot, Chief AI Governance and Ethics at DigiDiplomacy, Associate Partner at Meines Holla & Partners, and Alexandra Ebert, Chief Trust Officer at MOSTLY AI


    9:50–10:35 

    Leading with AI: Leadership Insights on Driving Successful AI Transformation

    Chandra Donelson, Chief Data and Analytics Officer at United States Air Force, Semih Kumluk, Head of AI and Digital at PwC, and Giorleny Altamirano Rayo


    10:50–11:35 

    The Future of Programming: Accelerating Coding Workflows with LLMs

    Michele Catasta, VP of AI at Replit, Jordan Tigani, CEO at Mother Duck, and Ryan J. Salva, VP of Product at GitHub


    11:40–12:25 

    Hugging Face and the Future of the Open Source AI Ecosystem

    Julien Simon, Chief Evangelist at Hugging Face


    12:40–13:25 

    Building an AI Strategy: Key Steps for Aligning AI with Business Goals

    Vin Vashishta, AI Advisor and Founder of V Squared, Cindi Howson, Chief Data Strategy Officer at ThoughtSpot, and Sonali Bhavsar, Managing Director at Accenture


    13:30–14:15 

    Charting the Path: What the Future Holds for Generative AI
    Edo Liberty, CEO at Pinecone, Tomasz Tunguz, General Partner at Theory Ventures, and Nick Elprin, CEO at Domino Data Lab


    14:20–15:05

    Closing Session & AMA

    DataCamp’s Co-founders, Jonathan Cornelissen, CEO, and, Martijn Theuwissen, COO

    Once again, RADAR AI is free for everyone

    Radar: AI is more than just another AI conference, but a place to connect with like-minded individuals and organizations. Whether you’re a data scientist, business leader, or just AI-curious, Radar: AI Edition offers something for everyone.


    Don’t let the data and AI revolution pass you by.

    Register Now

    Making tables in R with the gt package workshop

    Join our workshop on Making tables in R with the gt package, which is a part of our workshops for Ukraine series! 

    Here’s some more info: 

    Title: Making tables in R with the gt package

    Date: Thursday, June 13th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone) 

    Speaker: Rich Iannone, Rich is a software engineer that enjoys working with R and Python. He likes to create packages that help people to accomplish things. While Rich very clearly digs programming, he enjoys other things as well! Examples include: playing and listening to music, reading books, watching films, meeting up with friends, and wandering through the many valleys and ravines of the Greater Toronto Area.

    Description: The goal of the {gt} package is to make building tables for publication a hassle-free process while giving you the freedom to be creative. If you’re familiar with {ggplot2}, the feel of working with {gt} isn’t too far off. Join this workshop for background on the goals of {gt} and an extensive tour of its features by the package developer. There are a lot of functions in this package but we’ll go through the most important ones and learn how to make beautiful tables!

    Minimal registration fee: 20 euro (or 20 USD or 800 UAH)



    How can I register?



    • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

    • Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

    If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.


    How can I sponsor a student?


    • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

    • Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.


    If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).



    You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.


    Looking forward to seeing you during the workshop!

    DataCamp Sale: Get 50% off unlimited data and AI learning

    Transform your career with vital data and AI skills.

    Designed for all levels—whether you’ve never written a line of code or you’re an advanced data science practitioner—secure half-price learning across the world’s most in-demand data and AI skills.

    Save Now


    What do I get with a DataCamp Premium Subscription? 

    480+ interactive courses for all levels

    From generative AI basics to advanced programming and Business Intelligence tooling, unlock DataCamp’s entire interactive course library: including Python, ChatGPT, SQL, Power BI, and more

    Tailored Career and Skill Tracks

    Take the stress out of learning with bespoke learning paths. Start from scratch and develop job-ready skills built for in-demand career personas, such as Data Scientist/Analyst in Python, Data Analyst in SQL, Machine Learning Scientist, and more.

    Forbes’ #1 Ranked Certification Program

    Developed with industry leaders, enhance your CV with DataCamp’s Certification program. From data and AI Fundamentals to Technology Certifications in Tableau, Power BI, and Alteryx to career-ready Data Scientist, Analyst, or Engineer options—find a route that suits your ambitions.

    And much more. Gain unlimited access to DataCamp’s entire platform for half price.

    Limited time only. Only valid for annual subscriptions for maximum savings.

    Discover more

    DataCamp Launches DataLab: An AI-Enabled Data Notebook

    DataCamp is launching DataLab, an AI-enabled data notebook to make it easier and faster than ever before to go from data to insight, regardless of technical ability.

    The challenge DataLab Solves

    DataCamp’s mission to democratize data skills has translated into its leading online data and AI learning platform. 

    Alongside learning, intuitive data tooling is vital for modern professionals to feel empowered to make data-driven decisions. But more often than not, tools today are getting in the way rather than helping us. Depending on your skill set, you need different tools (Excel, a SQL editor, a Python notebook). 

    As a result, insights are scattered across functions and collaboration becomes a drag. And, insights are often separated by technical skills or needing to go through specialist data teams to get answers.

    The solution: Democratized insights

    DataLab is an AI-powered chat interface specifically tailored for data analytics. The steps are simple: attach a data source, ask a question, and iterate your way to the insight you need, just like you would with a technically skilled colleague.


    DataLab is an AI-powered data notebook to chat with your data

    DataLab’s key features:

    • Powered by code. The AI Assistant answers your questions by writing and running code and interpreting the outputs. With DataLab, you can seamlessly switch to a fully-featured notebook view with all of the generated code, that you can review, tweak, extend, and share.

    • Easy data access, wherever it lives. From CSV files and Google Sheets data to Snowflake and BigQuery: DataLab seamlessly and securely connects to all your data sources. DataLab’s AI architecture knows where to look and achieves best-in-class results by leveraging organizational knowledge, your previous activity, and industry best practices.

    • Built-in reporting. Forget about copy-pasting across tools or sharing outdated screenshots of your findings. As you’re getting answers to questions in DataLab, you’re accumulating a live-updating report that you can customize before sharing with others with a single click.

    DataLab’s chat interface looks similar to ChatGPT, and that’s the point! OpenAI managed to package extremely sophisticated technology into an intuitive interface. 


    Just because technology is complex, doesn’t mean the interface needs to be.

    DataLab’s path so far


    DataLab is the next iteration of DataCamp Workspace, an online data notebook with more than 50,000 monthly active users and support for SQL, Python, and R. 


    With the breakthrough of GPT-3.5 and many other LLMs in early 2023, DataCamp saw the opportunity to make their users even more effective and Workspace accessible to a bigger user base, both for study and work.


    DataCamp added powerful AI features to write, update, fix, and explain code. The built-in Workspace AI Assistant is smarter than ChatGPT: it takes more context into account (variables, table names, and column types), leading to higher-quality suggestions and a faster workflow. 


    DataLab is Workspace’s notebook environment plus an intuitive AI-powered chat interface. This means you’re getting the power of AI and a fully-fledged coding environment without switching tools. Real-time collaboration, scheduling, version history, role-based access control, you name it: you’re tapping into years of work building a data notebook that is intuitive and delightful to use, whether you’re learning on DataCamp or working through your unique projects.

    I have used Workspace in the past, what happens to my work?


    All your workspaces (now workbooks) you created in the past will stay available and continue to function. You can continue using DataLab for free (three workbooks, 20 AI Assistant prompts, basic hardware); all you need is your DataCamp account. 


    Users on an existing Workspace Premium subscription can access DataLab Premium, featuring unlimited workbooks, unlimited AI Assistant prompts, powerful hardware, and more.

    Try it out for free


    • Visit www.datacamp.com/datalab

    • Pricing: DataLab is publicly available now and free to try (up to 3 projects, up to 20 AI Assistant prompts). For $99/user/year you can create unlimited projects, use the AI assistant without limitations, and access more powerful hardware. See www.datacamp.com/datalab/pricing for more details.

    • Interested in leveraging DataLab to drive insight in business data? Book a demo