Data Science & Analytics with Python

Master data science with Python. Learn data cleaning, visualization, statistics, exploratory data analysis (EDA), and predictive modeling with real projects.

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1000+ Students
Advanced Level
40 Classes 15 weeks
India
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Course Description

Data Science is one of the most in-demand skills across industries like finance, healthcare, e-commerce, and technology. This course takes learners from data fundamentals to advanced analytics using Python.

You’ll learn NumPy, Pandas, Matplotlib, and Seaborn for data manipulation and visualization. Then, you’ll dive into statistics, hypothesis testing, machine learning basics, and predictive analytics.

With live mentor-led coding workshops for project guidance and pre-recorded tutorials for technical deep dives, this hybrid course ensures learners not only understand theory but also apply skills to real-world projects.

By the end, you’ll have built multiple projects, including a capstone predictive analytics project.

Target Audience

  • Beginners wanting to start a career in data science
  • Python learners moving into analytics
  • Students preparing for internships/jobs in AI/ML
  • Professionals upskilling for data-driven roles

Prerequisites

  • Python programming basics (variables, loops, functions, OOP)
  • Basic math & statistics recommended

Learning Outcomes

By completing this course, learners will:

  • Use NumPy & Pandas for data cleaning and manipulation
  • Visualize data with Matplotlib & Seaborn
  • Perform statistical analysis and hypothesis testing
  • Conduct exploratory data analysis (EDA)
  • Build predictive models using Scikit-Learn
  • Apply real-world analytics in domains like business, finance, and marketing
  • Present insights with data storytelling techniques

 Live Components

  • Weekly mentor-led EDA & ML project reviews
  • Group data analytics projects
  • Capstone project presentation with feedback

Pre-recorded Access

  • Tutorials for NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn
  • Ready-to-use datasets & Jupyter notebooks
  • Revision videos for each module

Amar Deep Rao

Instructor Photo
  • 4 Instructor Rating
  • Good Reviews
  • 5000 Students
  • 900 Courses

Satendra Patel | AI and Robotics Instructor

Hey there! Learn with me in a gamified way.
Instructor Photo
  • 4.2 Instructor Rating
  • 100+ Reviews
  • 200+ Students
  • 10+ Courses

I am a Robotics Teacher with experience in teaching STEM concepts through hands-on, engaging lessons designed for young learners. I specialize in simplifying complex topics into practical, easy-to-understand activities that emphasize creativity, critical thinking, and real-world problem solving. I have successfully taught 200+ students aged 10–13 across India, the US, UK, and Canada using platforms such as Arduino, Raspberry Pi Pico, and Micro:bit. Along with teaching, I also contribute to curriculum design to make learning accessible and impactful.

Passionate about making technology learning exciting and future-ready, I am committed to preparing students through interactive methods and practical projects. My student-centric and detail-oriented teaching approach ensures that every learner feels supported and inspired.

Educational Qualification – B.Tech in Computer Science and Engineering from Lovely Professional University

Experience – 2+ year in NaivoTech, delivered live online and offline robotics sessions  

Vaseel Ahmad

Robotics Instructor
Instructor Photo
  • 4.5 Instructor Rating
  • 500+ Reviews
  • 1000+ Students
  • 20+ Courses

I am an educator at viLab with experience in teaching Robotics, AI and Coding. I specialize in simplifying complex technical concepts into engaging, hands-on lessons that make learning fun and practical for young learners. My classes emphasize creativity, critical thinking, and real-world problem solving, and I have successfully taught students across Lucknow using Arduino UNO and Pictograph.

Passionate about making technology education exciting and inclusive, I am committed to preparing students to become future-ready through interactive teaching methods and practical projects.

Educational Qualification – Pursuing B.Tech from Bansal Institute of Engineering and Technology, with a focus on coding skills.

Experience – Teaching experience in the field of Robotics and Coding, guiding students in building projects and developing problem-solving abilities.

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Data Science

What’s Included

Everything you need to know about this course

Lectures
40 Classes
Duration
15 weeks
Level
Beginner
Language
English / Hindi

What you need / Requirement

Audio/Video Essentials
Audio/Video Essentials

Headphone or Speakers for clear audio, Webcam & Microphone.

Software/Tools
Software/Tools

PDF Reader (for notes and study materials).

Internet Connection
Internet Connection

Stable Internet with at least 2 Mbps speed for smooth video streaming and interactive content.

Device
Device

Smartphone, Tablet, Laptop or Desktop Computer.

Your Journey. Your Growth.

A structured path designed to take you from basics to mastery with clarity, confidence, and real-world impact.

01

Beginner

Start with fundamental concepts and build a strong foundation.

02

Intermediate

Expand your knowledge and start building practical projects.

03

Advanced

Dive deeper into specialized areas and master complex techniques.

04

Master

Achieve expert-level proficiency and innovate with your skills.

Start Your Learning Journey

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Our curriculum is meticulously designed in collaboration with industry leaders to ensure every skill you acquire is not just current, but in high demand.

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Our mentors are seasoned professionals and thought leaders who provide unparalleled guidance and personalized feedback.

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YOUR ROADMAP

REGVA

A clear, step-by-step milestone path to take you from the basics to building real-world AI solutions.

01

Introduction to Data Science & Python

Your journey begins with learning what Data Science is and how Python is used to analyze and understand data. You’ll get familiar with essential libraries like NumPy, pandas, and matplotlib.

01
02
02

Collecting, Cleaning & Organizing Data

You’ll learn how to import datasets, fix missing or incorrect values, format data properly, and prepare it for analysis — the most important step in real-world data work.

03

Data Visualization & Interpretation

Time to make the data speak! You’ll create charts, graphs, and dashboards to identify patterns and trends using matplotlib and seaborn — turning numbers into clear insights.

03
04
04

Exploring Data Patterns & Insights

You’ll learn how to find relationships in data using statistics, correlation, grouping, and summaries. This helps you understand what the data is really telling you.

05

Build Predictive Models with Scikit-Learn

You’ll build your first machine learning models to make predictions — like forecasting sales or classifying categories — and evaluate their accuracy to ensure reliability.

05
06
06

Capstone Project & Portfolio Presentation

Finally, you’ll complete a real Data Science project — analyzing a dataset and presenting your findings. You’ll save your code and results in a portfolio that can be shown in interviews or presentations.

Got Questions?

Frequently Asked Questions

Everything you need to know about Data Science & Analytics with Python

A hands‑on path from data fundamentals to advanced analytics using Python, covering NumPy, Pandas, Matplotlib, Seaborn, statistics, hypothesis testing, ML basics, and predictive analytics.

Python basics (variables, loops, functions, OOP) and comfort with basic math/statistics; Jupyter/Colab familiarity helps but isn’t mandatory.

Modular lessons that move from data manipulation and visualization to EDA, statistics, and ML basics, with projects in each module and a capstone at the end.

Yes. Post doubts in the Doubts section or during live classes; mentors reply asynchronously or schedule a live 1:1/Group session if a detailed discussion is required, and doubts are typically resolved within 24–48 hours.

Certificate programs generally issue a completion certificate upon successfully finishing all required modules and assessments; external “certifications” (industry exams) are distinct and may require separate testing with a third party body.

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