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Fundamentals of Data Science

Accelerate your Career

Learn Python and data science foundations. Master programming basics, data analysis, visualization, and machine learning essentials in 90 days.

4 Modules
with Certifications
7:15 Hours
of Recorded Content
5.0 Ratings
by 5480 Learners
English
Language
Paid Course
Get this Course @ ₹799
5480 enrolled in this course

Fundamentals of Data Science

Fundamentals of Data Science is an Explorer-level course designed for learners who want to begin their journey into data analytics and machine learning. Starting with an introduction to data science and Python programming fundamentals, the course gradually introduces learners to powerful analytical libraries such as Pandas, NumPy, Matplotlib, and Seaborn. Participants also gain hands-on exposure to the complete data science workflow, including data collection, cleaning, exploratory data analysis, visualization, and basic statistical concepts. By the end of the course, learners will possess a solid foundation required for advanced studies in data science, machine learning, and artificial intelligence.
MASTERING THE DATA SCIENCE LIFECYCLE

Comprehensive Syllabus Outline

A comprehensive curriculum designed to take you from beginner to professional.

M1

Module 1 — Introduction to Data Science and Analytics

Introduction to Data Science Concepts, Applications and Career Pathways

M2

Module 2 — Python Programming Foundations

Python Programming Fundamentals for Data Science Applications
Working with Python Data Structures for Data Analysis
Core Python Programming Concepts for Data Science Workflows

M3

Module 3 — Data Science Libraries and Analytics Tools

Data Analysis using Pandas for Structured Datasets
Numerical Computing using NumPy for Data Analytics
Data Visualization using Matplotlib for Analytical Reporting
Python for data analytics - Seaborn

M4

Module 4 — Data Science Workflow and Statistical Foundations

Data Collection, Data Wrangling and Data Cleaning Techniques
Exploratory Data Analysis and Data Visualization Workflows
Probability and Statistics Foundations for Data Science

Capstone Project

Foundational Data Analytics Portfolio

Apply core data science concepts to explore, clean, analyze, and visualize datasets using Python and industry-standard analytics libraries.

A cleaned and preprocessed dataset ready for downstream analysis (Data Cleaning and Wrangling Exercise).
PROJECT

A cleaned and preprocessed dataset ready for downstream analysis (Data Cleaning and Wrangling Exercise).

Access hands-on simulation modules to master production level engineering challenges.

An Exploratory Data Analysis Report highlighting key insights, statistical summaries, and interactive charts (Exploratory Data Analysis Report).
PROJECT

An Exploratory Data Analysis Report highlighting key insights, statistical summaries, and interactive charts (Exploratory Data Analysis Report).

Access hands-on simulation modules to master production level engineering challenges.

A fully documented Jupyter Notebook integrating clean code, structural markdowns, and visualizations in Pandas and NumPy (Python Data Analytics Notebook).
PROJECT

A fully documented Jupyter Notebook integrating clean code, structural markdowns, and visualizations in Pandas and NumPy (Python Data Analytics Notebook).

Access hands-on simulation modules to master production level engineering challenges.

CORE TOOLING MASTERY

Tech Stack

Master the primary professional software development packages and workflow tools.

Python
Pandas
NumPy
Matplotlib
Seaborn
Jupyter Notebook
Anaconda
Career Impact

After this Course, You will be Able to

Observe the real-world utility outcomes you gain after program completion.

Understand the complete data science lifecycle and workflow.
Write Python programs for analytical and data processing tasks.
Work efficiently with Python data structures and programming fundamentals.
Perform data manipulation using Pandas and numerical analysis using NumPy.
Create professional visualizations using Matplotlib and Seaborn.
Conduct exploratory data analysis to identify trends and patterns.
Apply probability and statistical concepts in practical data science scenarios.
Build a strong technical foundation for advanced machine learning and AI studies.

Course Stats

₹10.5 LPA

Average Salary

₹38 LPA

Highest Salary

120%

Salary Hike

9,500+

Job Vacancies

Key Features

Mentorship

Receive guidance and insights from industry experts

Hands-on Experience

Gain practical skills in a real-world cutting-edge projects.

Networking

Connect with professionals and peers in your field

Skill Development

Enhance your technical and soft skills

Career Advancement

Boost your resume with valuable experience

Dual Certificate

Get a certification to showcase your achievements
DIGITAL VERIFIABLE CREDENTIAL

Let Your Certificates Speak For You

Our certification formally validates your skill set in recruiter searches with unique QR code verification and LinkedIn-ready structures.

Unique Credential ID & QR Code
Recruiters can scan to instantly verify your project files, source repository, and official completion marks.

Linkedin Certified Recognition
Easily push to your Linkedin profile with 1-click credential linking to increase high-end corporate recruiter views.

Certificate Sample
Status
Verified

Where Our Learners Work

Our alumni are driving innovation at the world's most prestigious technology companies.

Flipkart
Freshworks
Juspay
Chargebee
Zoho
PayPal
PREMIER PLATFORM EXPERIENCE

Why Pantech?

An expert-crafted learning infrastructure built for technical fluency.

Industrial Expert Mentors

Direct guidance and weekly doubt clearing sessions hosted by hardware, embedded, and software engineering veterans.

24/7 Interactive Support

Ask coding doubts anytime on our student community workspace and receive instant assistance.

Self-Paced Learning Engine

Access lifetime recorded modules with adaptive pacing to balance academics and professional work.

Career Guidance Support

Exclusive resume review, mock interviews, and placement assistance from industry experts.

We are Accredited by

Our Awards & Achievements
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VERIFIED STUDENT REVIEWS

What Our Students Say

See how Pantech courses accelerated career transitions across India.

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Get exclusive lifetime access to coursework, simulators, custom templates, and direct placement opportunities.

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HAVE QUESTIONS?

Frequently Asked Questions

Find instant answers to all common questions about our technical certificate courses.

1. Do I need prior experience?

No prior experience is required for foundational courses. Advanced modules may recommend basic knowledge in programming or electronics.

2. What if I face technical issues?

You can reach our support team at training@pantechelearning.com or call +91 89255 334 88 / +91 89255 334 89.

3. What will I learn in this course?

You’ll cover Python and data science foundations, including programming basics, data analysis, visualization, and machine learning essentials. You’ll gain hands‑on experience with libraries such as NumPy, Pandas, Matplotlib, and Scikit‑Learn.

4. How long is the course?

The program includes 3 structured modules, designed to be completed within 90 days with guided project work.

5. Will I get a certificate?

Yes, upon completion you’ll receive a verified certification from Pantech eLearning, which can be shared on LinkedIn and with employers.

6. What is the course fee?

The Python and Data Science Foundations course is available for ₹799, inclusive of all modules and certification.

7. Is there any project work included?

Yes, you’ll apply your skills in a guided data science mini‑project to reinforce concepts and demonstrate practical learning outcomes.

8. Can I access the course materials anytime?

Absolutely. Once enrolled, you’ll have lifetime access to the course videos, notes, and resources.

9.Which tools and libraries are covered?

Learners gain experience with Python, Pandas, NumPy, Matplotlib, Seaborn, Jupyter Notebook, and Anaconda.

10.Does this course include practical exercises?

Yes. Learners work on data cleaning, exploratory data analysis, visualization tasks, and Python-based analytical exercises that build a strong foundation for future data science projects.

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