Data Analysis

Take your first steps to become a fully qualified data analyst by learning how to explore large relational datasets.

Build reporting applications and dashboards using the different MicroStrategy objects

Explore Python frameworks like pandas, Jupyter notebooks, and Matplotlib to build data pipelines and data visualization

Create and share livecode, equations, visualizations, and explanatory text, in both a single document and a web browser with Jupyter

Become familiar with Kubernetes and explore techniques to manage your containerized workloads and services

Add a touch of data analytics to your healthcare systems and get insightful outcomes

Collect and scrape different complexities of data from the modern Web using the latest tools, best practices, and techniques

Build efficient forecasting models using traditional time series models and machine learning algorithms.

Leverage the full potential of SAS to get unique, actionable insights from your data

Learn exploratory data analysis concepts using powerful R packages to enhance your R data analysis skills

Master scala's advanced techniques to solve real-world problems in data analysis and gain valuable insights from your data

Get to grips with pandas - a versatile and high-performance Python library for data manipulation, analysis, and discovery

Get to grips with the most popular Python packages that make Data Analysis possible

Understanding the concept Dark Web and Dark Net to utilize it for effective cybersecurity

Learn how some Go-specific language features help to simplify building web scrapers along with common pitfalls and best practices regarding web scraping.