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Jonathan Cornelissen
Co-founder and CEO of DataCamp
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Alex Blackman
Senior Enterprise Product Marketing Manager
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DataCamp: Q2 2021 Roadmap

November 2021

Summary

In the DataCamp Q2 2021 Roadmap webinar, major developments and future plans for DataCamp were discussed, focusing on overcoming challenges to a data-proficient world. The session identified three main obstacles: the high cost of data science education, the labor market's imbalance in data professionals, and the lack of collaborative data science tools. DataCamp's vision is to address these issues through DataCamp 2.0, which includes data science certification, data science career services, and enhanced data science collaboration tools. The webinar highlighted recent feature releases such as free Signal data skill assessments, the organization's Skill Matrix, and new data science courses, including Tableau and data privacy. Additionally, improvements in mobile app design and active learning methods were discussed to boost continuous learner engagement. The enterprise team is also improving admin functionalities and reporting tools to measure learning ROI effectively. The focus remains on expanding DataCamp's offerings to ensure comprehensive data science skill development, easier career transitions in data science, and improved collaborative capabilities for data professionals.

Key Takeaways:

DataCamp aims to overcome educational cost barriers, labor market imbalances, and lack of collaboration tools in data science.
DataCamp 2.0 focuses on data scientist certification, data science career services, and new data science collaboration tools.
Recent releases include free Signal data skill assessments and an organizational Skill Matrix.
New data science courses in Tableau and data privacy have been introduced.
Improved mobile app design and interactive learning methods aim to boost learner engagement in data science.

Deep Dives

Overcoming Educational Cost Barriers

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One of the core themes of the webinar was the high cost of data science education, considered a significant obstacle to achieving a data-literate world. DataCamp aims to tackle this by offering more accessible education through innovative solutions. The introduction of free Signal data skill assessments is a step in this direction, allowing both free and paid members to evaluate their skills without additional costs. This move broadens access to learning paths, enabling learners to assess their competencies in Python, SQL, and R, among others, without financial constraints. The company's commitment to providing affordable education aligns with its mission to increase data literacy. “Education shouldn’t be a privilege but a right,” said Jonathan Cornelison, CEO of DataCamp, emphasizing their dedication to making quality data science education accessible to all.

Addressing Labor Market Imbalances

Another critical challenge identified is the labor market's imbalance concerning data professionals. The demand for skilled data scientists far exceeds supply, causing inefficiencies and high costs for businesses. DataCamp’s response involves launching data scientist certification and job placement in data science to bridge this gap. The new professional data science certification aims to validate learners' skills, making them more appealing to potential employers. Personalized career coaching and expert resume preparation are also part of this initiative, designed to transition learners from “learning to earning.” This approach not only benefits individuals seeking jobs but also aids businesses in identifying qualified data talent, thus enhancing recruitment efficiency.

Enhancing Collaborative Tools for Data Professionals

The lack of collaboration tools in data science was another prominent topic. DataCamp plans to develop its Workspace product to facilitate easy collaboration among data professionals. This feature allows users to work together in real time, similar to the ease of Google Docs. By supporting popular editors like Jupyter Labs and RStudio, Workspace aims to simplify the transition from learning to practical data science work. It encourages sharing insights and collaborative projects, which are essential in a data-driven industry. As Alex Blackman pointed out, "Collaboration should be as easy as opening a Google Doc," highlighting the focus on making data science work more inclusive and team-oriented.

Interactive and Engaging Learning Experiences

The webinar stressed the importance of interactive learning experiences as a differentiator for DataCamp. Unlike platforms that heavily rely on video-based content, DataCamp emphasizes active learning through interactive exercises and projects. This approach has led to higher course completion rates, as learners remain engaged and can apply their knowledge practically. The improved mobile app also supports this learning style, offering short, engaging lessons to maintain momentum outside traditional settings. The introduction of data science awareness courses on mobile caters to non-coders, expanding DataCamp's reach and encouraging a broader audience to explore data science. “Active learning keeps our learners engaged and ensures they complete data science courses,” noted Jonathan Cornelison, emphasizing the value of this method.