Python for Data Analytics
Why You’ll Learn Python for Data Analytics
In today’s data-driven world, Python is the top programming language for analytics. Organizations across industries-finance, healthcare, marketing, logistics, and technology-use Python to extract insights, make smarter decisions, and automate tasks. By learning Python for Data Analytics, you open doors to exciting roles such as Data Analyst, Business Analyst, Data Scientist, and AI Engineer.
Program Overview
- KTitle: Python for Data Analytics (Certificate Program)
- KDelivery: Hybrid (Online or Onsite), Part-Time
- K Duration: 40 hours (flexible schedule over evenings/weekends)
- K Audience: Beginners to Intermediate learners, no prior coding experience required
- KCredential: Certificate of Completion, co-signed by industry experts
This program combines theory + hands-on activities + real-world projects, ensuring participants walk away with practical, job-ready skills
Industry Insights
- KThe most in-demand Python libraries and tools used in real jobs
- KHow businesses make decisions using data analytics
- KCommon challenges in industry projects (dirty data, shifting goals, time constraints)
Types of Projects You’ll Work On
- KCustomer behavior analysis for an e-commerce company
- KSales and revenue trend analysis for a retail chain
- KPredictive modeling for healthcare outcomes
- K Visual dashboards for marketing campaign results
- KOperations and supply chain efficiency analysis
Learning Outcomes
- KWrite Python scripts to analyze data sets
- KClean, transform, and prepare data for analysis
- KCreate visualizations and interpret findings
- KApply statistical methods to real-world problems
- KUnderstand the basics of predictive modeling
Program Delivery Options
- KOnline: Interactive live sessions + recorded lectures + hands-on labs
- KOnsite: In-person workshops at our training center
- KHybrid: Mix of online and in-person, with flexible options for busy professionals
Who Should Join?
- KAspiring Data Analysts, Business Analysts, Junior Data Scientists
- KCareer switchers looking to enter the data-related field
- KProfessionals seeking to upskill in analytics and Python
- KStudents and recent graduates wanting a competitive edge
Certification Details
- KOfficial Certificate of Completion
- KRecognition from industry experts and hiring partners
- KA portfolio-ready final project to showcase to employers
Modules in This Program
Introduction to Python
– Python basics: variables, data types, loops, conditionals
– Writing clean, efficient Python code
Working with Data
– Numpy for numerical computing
– Pandas for data manipulation and analysis
– Reading data from CSV, Excel, databases, APIs
Data Cleaning and Preparation
– Handling missing values
– Data transformations
– Feature engineering techniques
Data Visualization
– Using Matplotlib and Seaborn
– Creating clear, insightful plots and dashboards
– Storytelling with data
Statistical Analysis and Insights
– Descriptive statistics
– Correlation, distributions, hypothesis testing
– Drawing insights from data
Introduction to Machine Learning
– Building simple models (linear regression, classification)
– Using Scikit-learn
– Understanding model evaluation
Final Project & Capstone
– Choose a real-world dataset
– Apply all learned techniques: clean, analyze, visualize, and present insights
– Final presentation + certificate award