End-to-End Analysis
Collect, clean, analyze and visualize data, then turn your findings into a clear, actionable report.
Self-Paced Bootcamp with Recorded Lessons
Python for Data Analysis & Business Intelligence Bootcamp | In Partnership with Cisco
A recorded, project-based bootcamp you can follow on your own schedule. Start with Python fundamentals, move into data analysis with Pandas and NumPy, SQLite and ETL, then build an interactive Streamlit dashboard. You can ask the instructor questions when you need guidance.
🐍
Try an interactive preview of what you will learn ↗
Build practical skills and portfolio-ready projects.
Learn to collect, clean, analyze and visualize data, and automate reports using Python in ways that reflect real workplace needs.
0Hands-On Projects
PythonAnalytics & Automation
CiscoCisco Training Partnership
3Months of Follow-up Support
What Will You Learn?
Essential Python Skills for Data Analysts
A practical curriculum that makes Python a tool for analyzing data, building reports and automating work—not just a programming language.
Clean, Well-Organized Python Code
Write maintainable code using functions, modules, logging and well-structured projects.
Pandas & NumPy
Work with CSV and Excel, clean data, use GroupBy, Pivot and joins, and perform numerical analysis.
ETL & Streamlit
Retrieve data from APIs, build simple ETL workflows and create interactive dashboards.
Interactive Learning Preview
From Your First Python Line to an Interactive Dashboard
Select a learning stage to explore simple code and a visual example of the skills covered in this recorded bootcamp.
Python Fundamentals
Start with lists, loops and core programming concepts.
sales = [120, 180, 240, 310]
total = sum(sales)
print(total) # 850
Total sample sales
850
Sample sales across 4 months (units)
Educational illustration using sample values—not live data or actual Python execution.
Data Analysis with Pandas
Clean data and transform it into clear, usable metrics.
import pandas as pd
df = pd.read_csv("sample_sales.csv")
monthly = df.groupby("month")["revenue_k"].sum()
print(monthly.sum()) # 129
Illustrative total revenue
129K
Monthly revenue in thousands (K SAR)
Educational illustration using sample values—not live data or actual Python execution.
Data Automation & ETL
See how data batches can be combined and processed.
batches = [150, 250, 350, 500]
clean_records = sum(batches)
print(clean_records) # 1250
Processed sample records
1,250
Illustrative batch sizes (records)
Educational illustration using sample values—not live data or actual Python execution.
Interactive Streamlit Dashboard
Discover how to display key metrics and charts in one app.
import streamlit as st
orders = [24, 36, 41, 59]
st.metric("Total orders", sum(orders))
st.bar_chart(orders)
Illustrative orders
160
Orders across four months (orders)
Educational illustration using sample values—not live data or actual Python execution.
Why This Bootcamp?
More Than Learning Python Libraries
Companies need people who can turn data into practical outcomes: gather and clean it, perform meaningful analysis, and automate repeatable reports. This recorded bootcamp is designed around the skills required to build end-to-end solutions with Python.
1
Start with the Fundamentals
Python syntax, variables, conditions, loops, functions, file handling and error management.
2
Analyze Real-World Data
NumPy, Pandas, CSV/Excel, data cleaning and discovering useful metrics and insights.
3
Connect SQL & APIs
Use SQLite through Python, write analytical queries and build a mini ETL workflow from an API to a report.
4
Showcase Your Project
Create a Streamlit dashboard, organize a GitHub portfolio, write a professional README and prepare for interviews.
Curriculum
Practical Bootcamp Modules
Ten progressive modules take you from preparing your workspace to building dashboards and completing portfolio-ready projects.
Showing 10 of 10 modules
01
Professional Development Environment Setup
- Python, venv, pip and requirements files.
- Jupyter and VS Code workflows.
- Git, GitHub and project file organization.
02
Python Fundamentals
- Syntax, variables and data types.
- Conditions, loops and functions.
- File handling and error handling.
03
Data Structures & Maintainable Code
- Lists, tuples, sets and dictionaries.
- Comprehensions and modules.
- Logging and an introduction to testing.
04
NumPy for Numerical Analysis
- Arrays and vectorization.
- Broadcasting and aggregations.
- Statistical functions and simulation.
05
Data Processing with Pandas
- Read CSV/Excel files and export results.
- Data cleaning, GroupBy and Pivot.
- Merging data and identifying insights in a notebook.
06
SQLite with Python
- Tables, keys and relationships.
- Joins, subqueries and window functions.
- sqlite3 and pandas.read_sql.
07
Visualization & Storytelling
- Choose the right chart for the question.
- Practical Matplotlib and Seaborn.
- Insights and actionable recommendations.
08
APIs + ETL + Report Automation
- Requests, parameters and pagination.
- Extract / Transform / Load.
- Automated Excel/CSV reports and charts.
09
Streamlit Dashboards
- Layouts, filters and KPIs.
- Charts, tables and caching.
- Optional: publishing your application for others to view.
10
Portfolio & Interview Readiness
- A professional README and screenshots of your results.
- Presenting projects as Problem → Results.
- CV, LinkedIn and Python/Pandas/SQLite interview questions.
No modules match your search. Try another term or choose All Modules.
01
Salary Statistics Analysis
- Read files and conduct a basic analysis.
- Salary statistics and performance indicators.
02
Expense Tracker
- Functions and code organization.
- Export Report.
03
Employee Data Organizer
- Data structures and modules.
- Organize employee records.
04
Financial Calculations
- NumPy and aggregations.
- Numerical financial analysis.
05
Sales Performance Report
- Pandas, KPIs and cleaning.
- Sales performance report.
06
Customer Segmentation
- GroupBy and Pivot.
- Insights and customer segmentation.
07
SQLite Analytics with Python
- Joins and window functions.
- Analyze query results in Pandas.
08
Market Trends Visualization
- Charts and storytelling.
- Turn analysis into a clear story.
09
Mini ETL from an API
- Extract, clean and save data.
- A repeatable automated report.
10
Streamlit Dashboard
- Interactive monitoring dashboard.
- A project you can demonstrate and run.
Effective Self-Paced Learning
The lessons are recorded so you can study on your own schedule. After enrollment, the team will explain how to contact your instructor when you have questions.
Instructor Support
When you run into a difficulty, send your question to the instructor for guidance on the concept or code so you can keep progressing.
Hands-On Practice
Complete practical exercises and projects, with feedback on your code when needed to strengthen your understanding.
3 Months of Post-Completion Support
Continue receiving help with questions and professional development for three months after completing the bootcamp.
Bootcamp Instructor & Education Consultant
Eng. Mostafa Nabih
Specialist in Data Analytics, Data Engineering & Career-Focused Training
Mostafa Nabih is an education consultant at Athar Academy with more than seven years of experience training learners in Data Analytics and Data Engineering. He holds Microsoft PL-300 and DP-700 certifications and achieved second place in an African artificial intelligence competition. His teaching emphasizes practical projects, understanding the tools and applying them to real-world challenges.
PL-300Microsoft Power BI Data Analyst certification
DP-700Microsoft Fabric Data Engineer certification
7+ YearsTechnical training and educational guidance
Learning format: Recorded lessons you can study on your own schedule, with the option to ask questions and request instructor guidance when needed. No fixed live-session attendance is required.
What Will You Be Able to Do?
By the end of this path, you will be able to complete a Python data analysis workflow, work with CSV/Excel, SQLite and APIs, build reports and dashboards, and prepare a professional GitHub portfolio to present your skills in interviews.
Bootcamp Benefits
Flexible Learning Focused on Real Outcomes
Study through recorded lessons at times that suit you, build practical projects, receive instructor guidance and develop work you can showcase.
Certificates & Career Support
An Athar Academy certificate and a Cisco Networking Academy certificate, subject to the applicable completion requirements, plus a recommendation letter opportunity for outstanding participants.
Portfolio-Ready Work
Notebooks, reports, a dashboard and GitHub READMEs that help you showcase your projects professionally.
Realistic Data Challenges
CSV/Excel files, SQLite and APIs that reflect practical business data challenges.
Career Preparation
CV, LinkedIn and interview preparation focused on Python, SQLite, Pandas and project outcomes.
Join the Bootcamp
Start Building Practical Python & Data Analysis Skills
Ideal for anyone who wants to learn Python for analytics through recorded, self-paced lessons—from the basics to professional-looking reports, dashboards and projects.
- A progressive curriculum from beginner to hands-on application.
- More than 10 practical projects using realistic datasets.
- Flexible recorded lessons with instructor support for questions.
- Athar Academy and Cisco certificates, subject to completion requirements.
Current Enrollment Offer
ر.س500.00
ر.س250.00
Discount 50%
Save ر.س250.00 when you enroll now
Frequently Asked Questions
Before You Enroll
Quick answers about recorded lessons, support, projects and certificates.
Yes. Start with Python fundamentals and the development environment, then move step by step into NumPy, Pandas, SQLite, APIs and Streamlit.
Yes. The bootcamp consists of recorded lessons for flexible, self-paced study. Watch whenever it suits you and send your questions to the instructor when you need help understanding a concept or fixing code.
Examples include salary analysis, expense tracking, employee data organization, sales reports, SQLite analytics, ETL from APIs and an interactive Streamlit dashboard.
The course focuses on a GitHub portfolio, professional READMEs, reports, notebooks and a dashboard project you can showcase.
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Start Learning Python for Data Analysis & Business Intelligence
Learn Python, Pandas, SQLite, APIs and Streamlit, and build practical projects to showcase on GitHub and in interviews.