Resume

Intensive bootcamp focused on practical data science skills, covering the full data analysis lifecycle: from data collection and cleaning to the construction and implementation of predictive models. Key areas included:

• Advanced proficiency in Python, Pandas, NumPy, and data visualization.
• Statistical analysis using SciPy and statsmodels, including hypothesis testing (t-tests, Chi-square) and p-value interpretation.
• Implementation of supervised and unsupervised Machine Learning models.
• Application of Agile methodologies and analytical thinking to real-world datasets.
• Development of end-to-end projects designed to solve specific business problems.

Certification validating practical proficiency in SQL and PostgreSQL for designing, querying, and manipulating relational databases, applied to data analysis and real-world problem solving.

• Use of relational databases and set theory fundamentals.
• Mastery of aggregate functions, advanced filtering, sorting, and grouping.
• Implementation of subqueries and various JOIN types (outer, cross, and self joins).
• Data manipulation (insertion, updates, and deletion) adhering to data integrity and consistency best practices.
• Application of summary statistics and window functions in PostgreSQL.

This certification validates expertise in Agile principles, frameworks, and practices, with a practical focus on Scrum and Design Thinking to drive innovation, adaptability, and collaboration across diverse environments.

• In-depth understanding of the Agile Manifesto and its core values.
• Proficiency in key frameworks: Scrum, Kanban, and Lean Startup.
• Practical application of Scrum in both technical and non-technical contexts.
• Integration of Design Thinking with Agile methodologies to generate user-centric solutions.
• Focus on ethical responsibility in product design and development.