Certified Business Analytics with Python
32 Hrs Duration
10+
Modules
4+ Live project
Internship support
Interview Support
KOED Academy – Program Highlights
- 5+ Industry-Aligned Courses
Master core and advanced concepts across Data Science, Product Management, and Financial Modelling. - 32+ Hours of Applied Learning
Gain hands-on experience through practical assignments, projects, and tool-based training. - 8 Professional Development Units (PDUs)
Earn PDUs to showcase your commitment to continuous learning and upskilling. - 4 Real-World Projects
Work on actual business challenges to apply concepts in real-life scenarios. - 1:1 Mentorship Sessions
Receive personalized guidance from industry mentors to support your learning and career goals.
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Our Students are Placed in
Curriculum
Overview of Business Analytics
Types of Business Analytics
Importance and Applications
Business Analytics Process
Roles and Responsibilities of a Business Analyst
Descriptive Statistics
Probability and Distributions
Inferential Statistics
Correlation and Regression Analysis
ANOVA and Chi-Square Tests
Data Cleaning and Preparation
Formulas and Functions
Pivot Tables and Charts
Data Validation and Conditional Formatting
Dashboard Creation
Database Concepts and Relationships
SQL Queries
Joins and Subqueries
Aggregate Functions and Grouping
Views and Indexes
Python Basics
Data Manipulation with Pandas
Numerical Computation with NumPy
Data Visualization with Matplotlib and Seaborn
Introduction to Statistical Analysis
Connecting to Data Sources
Creating Visualizations
Dashboards and Stories
Filters and Parameters
Sharing and Publishing Reports
Data Import and Transformation
Building Reports and Dashboards
DAX Functions and Calculated Columns
Interactive Visualizations
Publishing and Sharing Insights
Understanding Data Distributions
Identifying Outliers and Anomalies
Feature Engineering
Data Correlation and Causation
Visualization Techniques for EDA
Supervised vs. Unsupervised Learning
Common Algorithms
Model Evaluation Metrics
Overfitting and Underfitting
Introduction to Scikit-learn
Project Planning and Proposal
Data Collection and Cleaning
Analysis and Modeling
Visualization and Reporting
Presentation of Findings
Skills Covered
Cluster Analysis
Analytics
CRISP Modeling
Linear Regression
Logistic Regression
Rule Analysis
Graphical Representation of Data
Data Structure
Job Roles
Business Architect
Business Intelligence Analyst
Business Systems Analyst
Management Consultant
Process Analyst
Systems Analyst
Tools Covered
Python
Numpy
Jupitar
panda
Matplotlib
Power BI
SQL
Tableau
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