Learn Python by solving real data problems and building portfolio-ready work.
Work with real-world style business datasets, clean and analyze raw data with Pandas, create professional visualizations, discover insights, and complete portfolio-ready projects. Learn through live guidance, practical code labs, instructor feedback, and an industry-tested curriculum.
This course focuses on practical application, guided work, and subject-specific projects.
Learning Outcomes
Write clean Python code for data analysis
Load and clean real-world datasets
Transform raw data with Pandas
Explore data and identify patterns
Create professional charts
Answer business questions
Extract useful business insights
Build portfolio-ready analysis
Communicate findings clearly
Present data-driven recommendations
Practical Skills
Project-Based Learning
Every major skill is connected to a practical exercise or project. Students work with realistic datasets, analyze business problems, generate charts, explain insights, and create portfolio-ready work.
Build real business projects—not just coding exercises. Each project produces analysis, visualizations, and business insights you can add to your portfolio.
Build a Python program that summarizes monthly sales performance for a small business.
Final output: Python script + sales KPI summary
You will create
Transform a messy customer dataset containing missing values, duplicates, inconsistent categories, and invalid fields.
Final output: Cleaned dataset + data-quality report
You will create
Analyze company sales data to identify growth trends, strong products, weak regions, and management opportunities.
Final output: Notebook + charts + KPI summary + recommendations
Example output students learn to create with Python
Explore which customer segments and contract types are associated with higher subscription churn.
Final output: Churn summary + segment chart + retention insight
Example output students learn to create with Python
Compare digital marketing channels and recommend where the next campaign budget should be focused.
Final output: Campaign notebook + KPI analysis + channel recommendation
Example output students learn to create with Python
Python is the tool. Solving real data problems is the goal.
Clean Python analysis.
Professional charts.
Analysis-ready business data.
Explain what the numbers mean.
Projects you can showcase.
Understand the concept.
Complete guided exercises.
Use realistic data.
Answer business questions.
Create clear charts.
Communicate insights.
Complete a project.
Complete the entire data analysis process using a realistic business dataset.
Students create
Programming and analysis.
Interactive coding and documentation.
Data manipulation.
Numerical operations.
Data visualization.
Understand the concept with examples.
Follow practical Python exercises.
Apply the skill to realistic data.
Create something you can keep.
Students receive guidance on their work.
Practice with business-style datasets.
Write and test Python yourself.
Begin with a problem, not only syntax.
Finish with tangible, reviewable work.
Join the next live cohort and start building practical Data Science projects.
Prerequisites
A laptop for in-class practice and project coding labs.
Basic computer confidence with files, web tools, and spreadsheets.
Commitment to attend live interactive sessions and complete homework.
No advanced mathematics or coding required for foundation tracks.
Target Audience
Cohort Logistics
Live cohort plus guided labs
8 weeks
Khmer and English
Contact an advisor on Telegram to confirm specific cohort start dates, schedule choices, and seat availability.
Faculty
Courses are prepared with bilingual Khmer and English explanations, guided code examples, and supportive feedback.
Certification
Credentials reflect live attendance, code assignments, project capstone submission, and instructor rubric review.
Live program attendance
Weekly assignment labs
Final project capstone
Instructor rubric evaluation
Enrollment Process
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Curriculum Structure
Interactive live sessions where concepts are coded live and reviewed with students.
Build demonstrable outputs: notebooks, dashboards, SQL warehouses, and ML models.
24/7 access to cohort recordings, datasets, assignments, and rubric grading.
Course Questions
No. Data Insight Cambodia programs are live instructor-led cohorts. Recordings and portal resources are provided to help students review between sessions.
Beginner programs start from scratch. Intermediate programs outline their recommended preparation during the 1-on-1 advisor consultation.
Students receive an official verifiable digital credential after completing the required live sessions, assignments, and final capstone review.
We support students with practical capstones, portfolio reviews, career consultation, and partner introductions.
Admissions Desk
Connect with Data Insight Cambodia on Telegram to verify schedule options, curriculum questions, and enrollment details.