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How DataCamp Empowered Mohammed's Journey from Theory to Application As a Risk Analyst in Finance

Learn how Mohammed used DataCamp to overcome his lack of confidence in applying SQL and Python to real-world tasks in Finance.
26 giu 2023  · 4 min leggi

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​​Risk Analysis involves a deep blend of statistical proficiency and business acumen, which often proves challenging when first starting an analytics role.

Learn how Mohammed, currently a Risk Analyst at Grant Thornton, gained the confidence to leverage Python and SQL on real-world risk use cases with DataCamp.

Becoming a Risk Analyst

Although Mohammed had a longstanding interest in statistics and data analysis, his journey truly began during his Master's in Engineering Management in Boston. During his studies, Mohammed discovered a specialization in data analysis that aligned with his interests and led him to get a job as a Risk Analyst at Granth Thornton, a leading tax audit & consulting firm.

However, at the beginning of Mohammed's journey, he didn't feel confident applying his Python and SQL skills to real-world financial tasks, especially when presenting results in customer-facing scenarios.

I started learning on DataCamp because I didn't know how to apply my data science skills to real-world finance use-cases.

Mohammed RizwanullahRisk Analyst at Grant Thornton

Discovering DataCamp

Grant Thornton has a vibrant learning culture, and Mohammed found DataCamp among the available learning providers. DataCamp stood out to Mohammed for its structured courses, interactive learning experience, expert instructors, and flexibility to learn at his own pace. The mobile application was a significant bonus, and Mohammed loved completing practice exercises to sharpen his knowledge on the go.

DataCamp is a convenient environment to jump in whenever you feel like learning.

Mohammed RizwanullahRisk Analyst at Grant Thornton

After completing the Finance fundamentals in Python track, Mohammed was able to do a Time series modeling project for an insurance client and was really motivated to continue learning.

Once I completed a couple of courses related to Finance on DataCamp, it was really useful for my client work. I went ahead and started exploring more topics related to data science.

Mohammed RizwanullahRisk Analyst at Grant Thornton

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Fondamenti di finanza in Python

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Acquisisci le competenze introduttive necessarie per prendere decisioni finanziarie basate sui dati in Python, utilizzando le librerie pandas, NumPy, statsmodels e pyfolio.
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Bridging the Application Gap in Data Science

The next challenge for Mohammed was getting hands-on experience in creating machine learning models. Although he had previously learned about machine learning from other learning providers, the application gap remained. To bridge this gap, he enrolled in DataCamp's Data Scientist in Python Career Track. Comprising 23 courses and six projects and taking almost 90 hours to complete, this track is one of the most comprehensive career tracks on DataCamp.

DataCamp's philosophy is "learn by doing," so Mohammed loved the emphasis on implementing what he's learning right in the browser. He was able to sharpen his machine learning skills with interactive course exercises, notebook-based projects specifically designed on real-world datasets, and by practicing in the mobile app. Later on, he was able to present similar projects in customer-facing scenarios as well.

Become a Data Scientist with DataCamp!

Mohammed never stops learning. Having completed over 250 courses and projects on DataCamp, he believes that to be a high-value professional, he must continuously sharpen his skills. He is currently learning Power BI, Tableau, Excel, and SQL, besides Python-focused courses.

As I am in the data science field, I need to be aware of all the technologies so that I bring value to the work environment.

Mohammed RizwanullahRisk Analyst at Grant Thornton

Now Mohammed does a combination of Data Science and Data Analytics, including creating dashboards, statistical testing, and building machine learning models for customers.

DataCamp was valuable for all the client-facing work I do.

Mohammed RizwanullahRisk Analyst at Grant Thornton

Mohammed also appreciates the competitive DataCamp leaderboard within his firm, which helped showcase his training progress during performance reviews.

Getting Certified as A Data Scientist

At Grant Thornton, DataCamp certifications are compulsory–but since Mohammed has completed a lot of learning on DataCamp, getting certified was straightforward. Mohammed completed timed assessments and seamlessly accessed the final practical case study via DataCamp Workspace. So far, he has gained Data Analyst Accociate and Data Scientist Accociate certifications and is now looking to level up to the Professional certifications this year.

Mohammed aspires to become a Data Scientist in the future, and he finds that DataCamp certifications will serve as a valuable credential to make that transition a reality.

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Advice for Aspiring Data Scientists

Mohammed recommends allocating a specific time each day, even if it's just 30 minutes, to training for those looking to juggle a busy work schedule and continuous learning. He also emphasizes the importance of balancing training with practice and ensuring you gain hands-on experience that you can apply directly to your work.

Conclusion

Mohammed's journey to mastering Python and SQL on financial risk applications showcases the transformative power of continuous learning with DataCamp. As a Risk Analyst at Grant Thornton, he initially struggled to apply his data science skills in customer-facing scenarios confidently. However, by completing over 250 DataCamp courses and projects, Mohammed bridged the application gap and excelled in his client-facing work. He gained expertise in Python, Power BI, Tableau, Excel, and SQL and got certified as Data Analyst and Data Scientist. Mohammed aspires to become a data scientist, believing that learning on DataCamp will be instrumental in his future career.

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Fondamenti di finanza in Python

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Acquisisci le competenze introduttive necessarie per prendere decisioni finanziarie basate sui dati in Python, utilizzando le librerie pandas, NumPy, statsmodels e pyfolio.
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