Training Course in Data Analysis and Visualization Using Python
This course introduces participants to data analysis and visualization using Python, one of the most widely used programming languages in data science today.
The course guides learners from data preparation and analysis to creating clear, effective visualizations using Python libraries such as Pandas, Matplotlib, Seaborn, and Plotly.
Course Overview
No summary details available for this course.
Introduction
This course introduces participants to data analysis and visualization using Python, one of the most widely used programming languages in data science today.
The course guides learners from data preparation and analysis to creating clear, effective visualizations using Python libraries such as Pandas, Matplotlib, Seaborn, and Plotly.
Duration
5 days
Who Should Attend
- Researchers and analysts
- NGO and M&E professionals
- Academics and graduate students
- Data enthusiasts and professionals transitioning into data science
- Anyone seeking to automate and scale their data analysis workflows
Training Methodology
- Instructor-led walkthroughs
- Hands-on exercises using real-world datasets
- Practice-driven approach with live coding
- Peer review and mini-projects
- Code templates, cheat sheets, and reusable scripts provided
Learning Outcomes (Course Objectives)
By the end of the course, participants will be able to:
- Load, clean, and explore datasets using Python
- Perform descriptive and exploratory data analysis (EDA)
- Create calculated fields and aggregate data
- Visualize data using static and interactive charts
- Tell data stories through Python notebooks and dashboards
- Automate basic analysis processes with scripts
Course Modules
Course Outline
Module I: Introduction to Python for Data Analysis
- Why use Python for data analysis and visualization?
- Setting up the environment: Jupyter, Google Colab, or VS Code
- Overview of key libraries: pandas, numpy, matplotlib, seaborn, plotly
- Loading data from CSV, Excel, or APIs
- Data Frames: structure, inspection, and navigation
Module II: Data Cleaning and Preparation
- Handling missing values
- Filtering, sorting, and subsetting data
- Data type conversion and parsing dates
- Merging and joining datasets
- Creating new columns (feature engineering)
Module III: Descriptive and Exploratory Data Analysis (EDA)
- Summary statistics and group-wise analysis (groupby)
- Distributions and frequency tables
- Detecting trends, outliers, and anomalies
- Creating custom metrics and calculated fields
- Automating analysis with reusable scripts
- Data exploration and manipulation with Python libraries (pandas, matplotlib)
Module IV: Python Data Visualization Techniques
- Plotting basics with Matplotlib and Seaborn
- Bar charts, line graphs, scatter plots, box plots, and heatmaps
- Multivariate visualizations: pair plots, correlation plots
- Creating interactive plots using Plotly
- Chart aesthetics, labels, and themes for clarity
Module V: Data Integration and Automation
- Working with APIs and web scraping for data acquisition
- Automating data cleaning and analysis tasks
- Connecting R and Python for combined workflows
Module VI: Data Storytelling and Final Project
- Creating a visual data story using Jupyter/Colab notebooks
- Structuring your analysis: titles, markdowns, inline visuals
- Exporting and sharing reports (HTML, PDF, or slides)
- Introduction to Dash or Streamlit (optional, for interactivity)
- Final project: complete end-to-end analysis and visualization on a real dataset
- Peer review and live presentations
Course Administration
This instructor-led training course is delivered using a blended learning approach comprising presentations, guided practical sessions, web-based tutorials, and group work.
Accreditation
Participants will receive a Tech For Development Certificate of Course Completion.
Training Venue
Held at the Tech For Development Training Centre.
Accommodation & Airport Transfer
Arranged upon request.
Email: letstalk@techfordevelopment.com
Phone: (+254) 790 824 179
Tailor-Made
Customised training available.
Payment
Send proof of payment to letstalk@techfordevelopment.com.
