The "Data Science & Big Data – Exam" course is designed to provide in-depth and practical training in analyzing large-scale data using advanced tools. The program covers programming languages such as Python and SQL, essential for data manipulation and analysis. Participants will gain skills in data cleaning, preparation, and exploratory data analysis (EDA), alongside foundational statistics and data visualization techniques to aid result interpretation. The course also introduces key Big Data ecosystem tools, including Spark and Hadoop, and essential concepts related to data warehouses and data lakes. Emphasis is placed on data governance and quality, critical for ensuring reliability and compliance in analyses. The curriculum culminates in an exam featuring complex practical cases like clickstream analysis, multi-source data normalization, data drift management, and quality monitoring, with a focus on current topics such as privacy by design, MLOps, and streaming data handling. This training is aimed at professionals and aspiring data scientists seeking to strengthen their technical and operational competencies in the Big Data field.
The pathway is designed for managers, executives, function owners, auditors and professionals. Lessons use validated minimum study time and a contextual tutor; assessments use server-side random selection of questions and answers, session-continuity controls, camera and local audio-activity monitoring during protected tests.
Traceability and reliability: integrity events are logged for authorized review; automated signals do not determine the result on their own.
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