From Excel to Python: A Senior Analyst's Journey to Data Science

Getting Technical Quickly

Sonia shared how she really enjoys using the platform and expects to continue using for her foreseeable future. She has completed over 30 courses, focusing primarily on Python and Data Science and has earned over 225,000xp on Datacamp, in 2024. Two courses in particular really stood out for her:

• Python Data Science Toolbox: This course helped her transition from basic Excel operations to writing functions in Python, bridging the gap between her analytical expertise and modern data science methods.
• Intermediate Importing Data in Python: Learning to combine data from multiple sources opened new analytical possibilities. She has enhanced her skills on importing, transforming and joining data. With these Sonia now feels more excited and confident about going beyond working her usual government databases and OECD statistics to widening the range of databases that she can access.

A Clear Path at Your Pace

Coming from a traditional analytics background, Sonia appreciated DataCamp's thoughtful approach to learning advanced technologies:

• Structured Modules: Starting with foundational concepts before moving to advanced topics helped her build confidence.
• Self-Paced Learning: This flexibility allowed her to balance learning data science with other pursuits, including French and Buddhism courses.
• Practice-First Approach: The immediate practice after each concept helped reinforce her learning. Being new to coding she really appreciates the several practice modules that the course/platform offers.

Working Directly with Data Scientists

For Sonia, gaining technical skills transforms her interactions with data science teams allowing her to:

• Understand and contribute to discussions about model selection and data preprocessing
• Review and critique complex data science methodologies
• Collaborate more effectively on cross-functional projects
• Bridge the gap between analytical insights and technical implementation

As she works toward certification, Sonia's journey shows that expanding your technical toolkit isn't just about learning new tools—it's about becoming a more effective collaborator in today's data-driven environment.

Sonia appreciates AI’s potential in enhancing data scientists’ work but sees how it conversely requires an even keener eye and understanding of the tools, methods and various inputs involved in working, with and presenting the findings, from data.