Non-IT Track: Data Science for Non-Programmers

Our Non-IT Track is specially designed for professionals without programming backgrounds who want to harness the power of data science in their careers. This program focuses on practical skills using user-friendly tools that don't require extensive coding knowledge.

Through our carefully structured 5-month curriculum, you'll develop the ability to analyze data effectively, create compelling visualizations, and make data-driven decisions that can transform your professional contributions and career trajectory.

Program Overview

Non-IT Track: Data Science for Non-Programmers

Duration: 5 Months

Structure: 3 months core + 1 month projects + 1 month finishing

Fee: ₹30,000

For: Professionals without programming background

Develop practical data analysis skills without extensive coding, master data visualization, and apply data-driven decision making in various domains.

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Course Objectives

✓ Develop practical data analysis skills without extensive coding
✓ Master data visualization and interpretation
✓ Learn to collaborate effectively with data science teams
✓ Apply data-driven decision making in various domains

Month 1: Data Literacy & Tools

4 Weeks

Data science fundamentals and terminology
Types of data and analytics
Data-driven decision making
Overview of data science workflow
Introduction to spreadsheet analytics
Advanced Excel/Google Sheets for data analysis
Formulas and functions
Pivot tables and data summarization
Data cleaning in spreadsheets
Database concepts
Basic SQL queries
Filtering and sorting data
Aggregations and grouping
Joins and relationships
Principles of effective visualization
Chart selection guidelines
Storytelling with data
Common visualization pitfalls

Mini Projects Lab Work

Month 2: PowerBI Essentials & Descriptive Analytics

4 Weeks

PowerBI Desktop installation and interface
Connecting to various data sources
Data cleaning with Power Query
Creating basic visualizations
Building your first dashboard
Data modeling in PowerBI
Creating calculated columns and measures
DAX formulas for business metrics
Custom visualizations
Drill through and filtering
Statistical measures and their interpretations
Distribution analysis
Correlation and association
Trend analysis and seasonality
Anomaly detection methods
Customer cohort analysis
Operational metrics and KPIs
Market basket analysis
Time series analysis basics
Creating executive summaries from data

Mini Projects Lab Work

Month 3: No-Code AI Tools & Business Intelligence

4 Weeks

Overview of no-code AI ecosystem
Automated machine learning platforms
Data preparation for no-code ML
Model evaluation without coding
Ethical considerations in AI
Building predictive models with KNIME/RapidMiner
Classification problems for business
Regression analysis for forecasting
Model interpretation and refinement
Deploying and sharing no-code models
BI strategy and framework
Dimensional modeling concepts
ETL processes and data warehousing
Self-service BI vs. enterprise BI
BI tool landscape and selection criteria
Requirements gathering for dashboards
KPI development and tracking
Interactive dashboard design
Data storytelling techniques
Presenting insights to stakeholders

Mini Projects Lab Work

Month 4: Capstone Project

4 Weeks

Problem definition and scoping
Data requirements identification
Project management for analytics
Stakeholder engagement strategies
Creating a project roadmap
Data sourcing and acquisition
Data quality assessment
Data cleaning and transformation
Creating an analytical dataset
Documentation best practices
Exploratory data analysis
Building an insight generation framework
Dashboard development
Creating a compelling data narrative
Continuous refinement based on feedback
Finalizing dashboards and reports
Creating implementation recommendations
Measuring impact and success
Knowledge transfer documentation
Preparation for final presentation

Project Development

Month 5: Finishing School

4 Weeks

Retail and e-commerce analytics
Healthcare analytics
Financial services applications
Manufacturing and supply chain analytics
Media and entertainment industry applications
Building an analytics portfolio
Data storytelling for non-technical audiences
Working effectively with technical teams
Interview preparation for data roles
Career paths in data analytics
Data ethics and privacy considerations
Augmented analytics trends
AutoML advancements
Natural language interfaces for data
Embedded analytics in applications
Comprehensive knowledge assessment
Capstone project presentation
Peer and instructor evaluation
Career action planning
Certification and next steps

Final Assessment

Contact Information

Edathena Academy

CIIC, Crescent Engg. College
Vandalur, Tamil Nadu 600048

+91-98403-47570
eda@edathena.com

Operating Hours
Mon – Fri 9:00AM – 6:00PM

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Recognition of Excellence

EdAthena awards verified Certificates of Completion to students who successfully finish their courses. Each certificate includes the learner's name, course details, lecture and practice hours, and a unique GUID for verification. Our certificates, recognized by employers and institutions, validate the learner's mastery of required skills through lectures, assignments, and evaluations.

Our certification program is designed in collaboration with industry experts and aligned with current market demands. Learners gain practical experience through hands-on projects and real-world applications, ensuring they're well-prepared for industry challenges. The certification not only demonstrates technical proficiency but also showcases problem-solving abilities and project implementation skills valued by employers.

Ready to harness the power of data without programming? Apply now to start your data science journey.

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