Data Science for Non-Programmers Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This beginner-friendly, no-code course introduces data science fundamentals through hands-on exercises in accessible tools like Excel, Google Sheets, and Google Data Studio. Over six modules, each designed to take approximately one week (around 5-7 hours per module), learners will gain practical skills in data cleaning, analysis, visualization, and insight communication. The course emphasizes real-world applications and storytelling, enabling non-programmers to make data-driven decisions confidently.
Module 1: Introduction to Data Science
Estimated time: 6 hours
- Data science lifecycle
- Problem framing
- Key terminology
- Defining a business problem
- Outlining a data-driven solution approach
Module 2: Data Wrangling & Cleaning
Estimated time: 6 hours
- Handling missing values
- Outlier detection
- Normalization techniques
- Cleaning datasets using Excel or Google Sheets
Module 3: Exploratory Data Analysis
Estimated time: 6 hours
- Summary statistics
- Pivot tables
- Chart selection best practices
- Identifying trends and anomalies
Module 4: Visual Analytics & Dashboarding
Estimated time: 6 hours
- Principles of visual design
- Interactive dashboards
- Storytelling with data
- Building dashboards in Google Data Studio or Power BI
Module 5: No-Code Predictive Modeling
Estimated time: 6 hours
- Regression vs. classification
- Model evaluation metrics
- Understanding overfitting
- Training models using no-code tools like RapidMiner or Orange
Module 6: Communicating Insights & Recommendations
Estimated time: 6 hours
- Crafting data narratives
- Slide deck design
- Stakeholder presentation skills
- Summarizing findings in a report and presentation
Prerequisites
- Familiarity with basic spreadsheet functions
- Access to Google Sheets or Microsoft Excel
- No programming experience required
What You'll Be Able to Do After
- Grasp core data science concepts without coding
- Perform exploratory data analysis using spreadsheets
- Build interactive dashboards for data visualization
- Train predictive models using no-code platforms
- Translate data insights into actionable business recommendations