Data Science with Python
Master the Foundations of Data Analytics in 4 Weeks
Learn Python, analyze data, and build a portfolio-ready capstone project through this fast-track, hands-on program.
Develop real data handling skills using industry-standard libraries and platforms. Ideal for beginners looking to break into data science, analytics, or tech-adjacent roles.
- 2 Years / Onsite
- Intakes: Jan, Apr, Jun, Oct
Overview
By the end of this course, students will have a solid command over Python’s key data science libraries and techniques. They will be capable of handling raw datasets, performing exploratory analysis, and visualizing patterns with confidence.
Participants will also understand the lifecycle of data science projects, from problem definition to solution presentation. Emphasis is placed on critical thinking and storytelling with data to support real-world decisions.
The program fosters independent analytical thinking and sets the stage for future upskilling in machine learning, data engineering, or applied statistics. Graduates leave with skills relevant to multiple sectors including retail, finance, logistics, and marketing.
- Duration: 4 weeks (live online)
- Mode: Instructor-led, interactive format
- Tools Covered: Google Colab, Python, Pandas, NumPy, Seaborn, Plotly
- Capstone: Exploratory Data Analysis of real business data from FoodHub app
Career Opportunities
This course opens doors to entry-level roles like Data Analyst, Junior Data Scientist, and BI Associate across sectors including finance, healthcare, and e-commerce.
Graduates gain practical Python skills, a portfolio-ready project, and hands-on experience with tools like Pandas, NumPy, and Plotly. It’s also a solid launchpad for advanced study in machine learning or business analytics.
Innova’s career team supports with resume feedback, internship leads, and skill-building for real-world hiring needs.
Program Learning Outcomes
By course end, learners will confidently use Python to clean data, perform analysis, and build visualizations using tools like Pandas, NumPy, Seaborn, and Plotly.
They’ll be equipped to manage end-to-end analytics tasks — from dataset exploration to insight presentation — while thinking critically and communicating clearly.
The course also prepares students for deeper specializations in AI, analytics, or domain-specific applications of data science.
What You’ll Learn
Weekly Breakdown
Week 1: Python Basics
Introduction to Python syntax, variables, data types, functions, and loops. Gain foundational coding skills with hands-on exercises.
Week 2: Pandas & NumPy
Learn how to manipulate and clean datasets using Pandas and perform numerical computations with NumPy arrays and functions.
Week 3: Data Visualization
Explore powerful plotting libraries like Seaborn and Plotly to build engaging, data-driven visual stories and dashboards.
Week 4: Exploratory Data Analysis
Dive into EDA techniques to summarize datasets, identify trends, handle missing data, and detect outliers using Python.
Entry Requirements
- No coding background required
- Open to students, working professionals, and beginners with analytical interest
Assessment & Progression
Weekly Assignments
Capstone Project
Certification
How to Apply
- Submit Application
Complete a short online form and select your preferred batch schedule.
- Receive Confirmation
Our team will guide you through next steps and course access.
- Start Learning
Join your live cohort and begin coding from Day 1.
Scholarship
Discounted seats available for students and early-career professionals. Referral-based and merit scholarships offered each cohort.
Your Pathway
to Global Careers
Our students create a vibrant and inclusive community
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