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Data Analysis and Machine Learning Fundamentals

Name: Data Analysis and Machine Learning Fundamentals
Rating: 0 (0 reviews)

Accelerate your Career

Learn essential data analysis and machine learning fundamentals. Gain practical skills in Python, statistics, and predictive modeling

Buy this Course @

₹1,499

5 Modules

with Certifications

9:00 Hours

of Recorded Content

0 Ratings

by 0 Learners

English

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Paid Course

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Email ID

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1500 enrolled in this course

Course Specifications

Sections

Lessons

Capacity

Unlimited

Duration

9:00 Hours

Students

2500

Access Duration

90 Days

Created Date

2 Jun 2026

Updated Date

3 Jun 2026

About Courses Certificate Benefits Requirements Testimony Bonuses FAQs

Data Analysis and Machine Learning Fundamentals Course
Overview

This Explorer-level course provides a practical introduction to data analysis and machine learning techniques used to transform raw data into actionable insights. Learners will explore data collection, cleaning, wrangling, exploratory data analysis (EDA), and visualization techniques, along with the statistical foundations required for data-driven decision-making. The course covers data preprocessing, handling missing values, feature engineering, and categorical data encoding before introducing supervised and unsupervised machine learning models. Participants will apply these concepts through real-world projects including credit score classification, stress prediction, social media advertising analysis, electricity price forecasting, and groundwater level prediction. By completing this course, learners will gain a strong understanding of the end-to-end machine learning workflow and predictive analytics methodologies.

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

We are Accredited by

Our Awards & Achievements

Data Analysis and Machine Learning Fundamentals Course Roadmap

Module 1

Module 1 — Data Science Workflow

Data Collection, Data Wrangling and Data Cleaning Techniques

Exploratory Data Analysis (EDA) and Data Visualization Techniques

Probability and Statistics for Data Science

Module 2

Module 2 — Introduction to Machine Learning

Introduction and overview of Machine Learning

Module 3

Module 3 — Data Preprocessing and Feature Engineering

Preprocessing Data for Machine Learning

Feature Selection and Feature Engineering Techniques

Handling Missing Values

Encoding the Categories Variable

Module 4

Module 4 — Machine Learning Models

Supervised learning Regression and Classification - Model

Unsupervised learning Clustering

Module 5

Module 5 — Classification and Prediction Projects

Credit Score Classification

Stress prediction using Machine Learning

Social Media Ads Classification

Electricity price prediction

Ground water level prediction

After this Course, You will be Able to

Grasp FPGA architecture and microcontroller workings for advanced understanding
Build circuits, ranging from basic LEDs to intricate, sensor-driven projects
Master the HDL IDE, enabling proficient coding for real-world applications
Utilize breadboards and electronic components with precision for efficient circuitry
Create groundbreaking solutions by integrating sensors and motors innovatively
Explore diverse projects, from basic LEDs to complex motion-activated systems

Where Our Students Work

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

Learners Reviews

Aditi Sharma

The step by step approach from basics to real time FPGA projects made the concepts crystal clear. I especially loved the UART implementation—it gave me confidence to handle hardware communication protocols.

Rahul

This course bridges the gap between theory and practice. Programming the MAX10 FPGA board and controlling GPIOs gave me the kind of exposure that’s directly useful for internships and entry level roles in VLSI design.

Priya Nair

I came in with only basic digital electronics knowledge. The way Verilog was introduced and gradually applied to sequential circuits and FSMs was perfect. By the end, I could write and test my own HDL codes on Quartus.

Still Having Doubts?

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 essential data analysis and machine learning fundamentals, including Python programming, statistics, data preprocessing, visualization, and predictive modeling. You’ll also gain hands‑on experience with libraries such as Pandas, NumPy, Matplotlib, and Scikit‑Learn.

4. How long is the course?

The program includes 5 structured modules, designed to be completed at your own pace, typically within 4–6 weeks.

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 Data Analysis and Machine Learning Fundamentals course is available for ₹1,499, inclusive of all modules and certification.

7. Is there any project work included?

Yes, you’ll apply your skills in a guided data analysis and ML 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.