Python for Data Analysis - Mastering Data Science Libraries for Actionable Insights, Impactful Decisions & Revealing Visualisations

Overview

🕮 Off the shelf (OTS)

This course is designed for professionals such as data analysts, financial analysts, quantitative analysts, data scientists, and others who aim to harness Python for data manipulation, analysis, and visualization tasks. It is particularly beneficial for those transitioning from tools like Excel or VBA to Python-based workflows.

No prior experience with Python is required; however, familiarity with basic data analysis concepts and tools is beneficial.

The Python Data Analysis Training Course offers a comprehensive introduction to Python programming with a focus on data analysis. Participants will learn to set up a Python environment, understand core programming concepts, and utilize powerful libraries such as Pandas and Matplotlib for data manipulation and visualization. The course emphasizes practical applications, enabling attendees to perform data cleaning, statistical analysis, and create insightful visualizations. Through hands-on exercises and real-world examples, learners will develop the skills necessary to apply Python effectively in data-driven roles.

Key Topics Covered:
• Setting up Python environments using Anaconda and Jupyter Notebooks
• Understanding Python core concepts: data types, control flow, functions, and file operations
• Working with dates, times, and accessing various data file formats (CSV, JSON, etc.)
• Data manipulation and analysis using Pandas
• Data visualization techniques with Matplotlib
• Applying statistical models and time series analysis for quantitative finance
• Real-world applications: portfolio optimization, asset pricing, and risk assessment
The course is delivered over three days and includes hands-on exercises to reinforce learning.