London, United Kingdom
By the end of this course, you will be able to:
- Confidently navigate the Python programming environment and write Python scripts to automate data analysis tasks.
- Construct effective SQL queries to retrieve, filter, and aggregate financial data from relational databases.
- Clean and prepare financial data for analysis using Python libraries like pandas.
- Apply EDA techniques to gain insights into financial data, including identifying trends, outliers, and correlations.
- Create clear and informative data visualizations using Python libraries to communicate findings to stakeholders.
- Utilize data analysis skills to solve real-world public sector finance and accounting problems.
Additional Information:
- Prerequisites: Basic understanding of financial accounting principles and spreadsheet software (Excel). No prior programming experience is required.
- Course Materials: Participants will receive comprehensive course materials, including lecture notes, lab exercises, and reference guides.
- Software: The course will utilize free and open-source software like Python, Jupiter Notebooks, and a popular SQL database management system (e.g., MySQL or PostgreSQL).
- This course equips senior public sector finance and accounting professionals with the necessary data analysis skills using Python and SQL to transform raw data into actionable insights, leading to more informed decision-making within the public sector.
- Python Programming Fundamentals
- Data Structures and Control Flow in Python
- Working with Financial Data in Python (pandas & NumPy)
- Writing SQL Queries for Financial Data Retrieval
- Data Cleaning and Wrangling with Python
- Exploratory Data Analysis (EDA) Techniques
- Data Visualization with Matplotlib and Seaborn
- Advanced Python Libraries for Finance (optional)
- Case Studies and Practical Exercises in Public Sector Finance
- Post-training Support and Q&A Sessions
- Coursework assignments and practical exercises throughout the program.
- Final project applying data analysis techniques to a real-world public sector finance scenario.
- Gain a solid understanding of the fundamental concepts of data analysis and its importance in the public sector.
- Become proficient in Python programming, including data structures, control flow, functions, and libraries like pandas and NumPy for financial data manipulation.
- Master SQL querying techniques to effectively extract and manage data from relational databases commonly used in the public sector.
- Develop skills in data cleaning and wrangling to prepare financial data for analysis.
- Learn to perform exploratory data analysis (EDA) techniques to uncover patterns and trends within financial datasets.
- Gain proficiency in data visualization using libraries like Matplotlib and Seaborn to create impactful charts and graphs to communicate insights effectively.
- Apply data analysis skills to real-world public sector finance and accounting scenarios through case studies and practical exercises.
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