How are AI-based tools used in the Data Analyst programme?
AI-based tools are viewed as valuable supplements that can enhance and accelerate tasks such as data analysis, feature engineering, and model building. While these tools provide significant efficiency gains, it’s important to understand that AI-generated outputs are not always free from errors.
As a data analyst, students are taught to critically evaluate, refine, and adapt AI-generated insights and code to ensure the accuracy of their analyses, robustness of models, and optimality of solutions. AI is seen as a support to their foundational knowledge, allowing them to work more efficiently while maintaining the integrity of their results.
How is AI used in the workplace as a data analyst?
AI is transforming how data analysts work by automating routine tasks like data preprocessing, model tuning, and even generating initial code for algorithms, which accelerates workflows. This allows professionals to focus more on innovative problem-solving and addressing complex analytical challenges.
However, a strong foundational understanding of the field is still crucial, as AI-generated outputs are not always flawless. The ability to critically evaluate, fine-tune, and adjust AI-driven solutions is key to ensuring accuracy, reliability, and precision in the final analysis or model deployment.
