Data Science Course with Placement Guarantee

Are you looking for a Data Science Course with Placement Guarantee? This course is designed for absolute beginners and professionals looking to build a career in Data Science, AI, and Machine Learning with 100% placement Guarantee.

Duration

6 Months

Next Batch

21 July 2025

Data Science Course(#113)

Name

Mobile

Country

Data Science Course Overview

Our Data Science Course is a job-focused program designed for beginners and professionals looking to transition into the field of data science. This course covers Python, Machine Learning, Deep Learning, AI, and Data Analytics, ensuring you master the skills top companies’ demand. Through hands-on projects and real-world case studies, you’ll build a strong portfolio to showcase your expertise to potential employers.

The demand for data science professionals is skyrocketing, with companies actively hiring data analysts, machine learning engineers, and AI specialists to make data-driven decisions. Whether you’re a fresh graduate looking for your first job or a working professional wanting to switch careers, our Data Science Course with Placement Guarantee will equip you with the right skills and job-ready experience to land a high-paying role in the industry.

You’ll get hands-on training with real-world projects, live industry case studies, and mentorship from experienced data scientists.

Why Choose Our Data Science Course with Placement Guarantee?

Our Data Science Course with Placement Guarantee is designed to help you master Python, Machine Learning, AI, Deep Learning, and Big Data; the most in-demand skills in today’s tech industry.

Here are some other reasons to join our data science course with 100 placement guarantee:

Learn from Experts – Get trained by industry professionals with real-world experience.
Hands-on Projects – Work on live datasets and real business problems.
100% Placement Support – Resume building, mock interviews & direct job referrals.
Globally Recognized Certification – Boost your resume with a valued credential.
Flexible Learning Options – Online, weekend, and self-paced batches available.
India’s Best Data Science Institute – PyNet Labs is considered the best institute for Data Science with job Guarantee.

Upcoming Batches

Data Science Course

DATE

TIME

SEATS LEFT

Batch 1
Weekdays Batch
(Monday to Thursday)
Starting from 21st July 2025

3 PM to 6 PM Indian Time
5: 30 AM to 8: 30 AM Eastern Time
9: 30 AM to 12: 30 PM UTC/ GMT00

Batch 2
Weekends Batch
(Saturday & Sunday)
Starting from 2nd August 2025

1 PM to 4 PM Indian Time
3: 30 AM to 6: 30 AM Eastern Time
7: 30 AM to 10: 30 AM UTC/GMT00

Upcoming Batches

Data Science Course

DATE

Batch 1
Weekdays Batch
(Monday to Thursday)
Starting from 21st July 2025

TIME

3 PM to 6 PM Indian Time
5: 30 AM to 8: 30 AM Eastern Time
9: 30 AM to 12: 30 PM UTC/ GMT00

SEATS LEFT

DATE

Batch 2
Weekends Batch
(Saturday & Sunday)
Starting from 2nd August 2025

TIME

1 PM to 4 PM Indian Time
3: 30 AM to 6: 30 AM Eastern Time
7: 30 AM to 10: 30 AM UTC/GMT00

SEATS LEFT

Start Your Data Science Journey Today!

Data Science Course Fees - ~~INR 84,500~~ INR 64,500/- Only
Easy EMI Options Available
(Complimentary English Classes)

What is Data Science?

Data Science is the process of extracting insights from data using programming, statistics, and machine learning. Businesses use data science to predict trends, automate processes, and make data-driven decisions. With the rise of AI and big data, data science has become one of the most in-demand career fields worldwide.

Why You Should Learn Data Science?

There are numerous benefits of doing the Data Science Course as Data Science is a very lucrative career. Here are a few reasons to learn Data Science:

High Demand & Salaries: Data Scientists earn an average of INR 10-25 LPA in India.

Job Security: Data-driven decision-making is the future of business.

Diverse Career Paths: Work in finance, healthcare, retail, marketing, and more.

Exciting Challenges: Solve real-world problems with cutting-edge technology.

Still wondering if data science is for you? Even non-programmers can learn with the right training!

Course Curriculum

Module 1 (8 Hours): Introduction to Data Analytics

Part 1: DATA ANALYTICS FOUNDATION

Data Analytics Introduction
Data Preparation for Analytics
Common Data Problems
Various Tools for Data Analytics
Evolution of the Analytics domain

Part 2: CLASSIFICATION OF ANALYTICS

Four types of Analytics
Descriptive Analytics
Diagnostics Analytics
Predictive Analytics
Prescriptive Analytics
Human Input in Various Types of Analytics

Part 3: CRIP-DM Model

Introduction to the CRIP-DM Model
Business Understanding
Data Understanding
Data Preparation
Modelling, Evaluation, Deploying, Monitoring

Module 2 (16 Hours): Microsoft Excel

Introduction to Excel Tables
Validations
Conditional Formatting
Advanced Filters
Hyper/Data Linking
Data Visualization and Dashboarding
Collaboration and Integration
Advanced Data Techniques
Macros and VBA Programming

Module 3 (8 Hours): Introduction to Statistics

Introduction to Descriptive Statistics
o Mean o Outlier o Median o Mode o Skew o IQR
Bivariate relation
Linearity, strength, direction
Slope of regression
Causality and correlation
Interpreting various graph formats:
o Dot Plot o Histograms o Box and Whisker o Scatter Plots

Module 4 (16 Hours): Introduction to Python

Working with Jupyter Notebook
Python concepts:

Print function
Variable
Loops
- If
- Else
- For
- While

Python Data Structures:
- Array
- Sets
- List
- Tuple
- Dictionary

Module 5 (16 Hours): Analytics using Python

Data cleaning
Data pre-processing
NumPy and Pandas Python Libraries
Data visualisation using Bokeh and Plotly
Data Analytics with Python
Case studies
Project

Module 6 (16 Hours): Power BI

Introduction to Power BI
Power BI Interface and Navigation
Connecting to Data Sources
Data Cleaning and Transformation
Advanced Transformations in Power Query
Data Modelling Fundamentals
DAX (Data Analysis Expressions) Basics
Advanced DAX Functions
Creating Basic Visuals
Advanced Visualizations
Mapping and Geospatial Visualizations
Custom Visuals and App Store
Designing Dashboards
Dashboard Interactivity
KPI Dashboards
Publishing and Sharing Reports
Collaborating in Power BI Service
Scheduled Refresh and Data Management
Advanced DAX and Calculations
Performance Optimization
Row-Level Security (RLS)
Case Studies

Module 7 (16 Hours): SQL

Introduction to Databases
What is SQL?
Installing MySQL
Creating the Databases
The SELECT Statement
The SELECT Clause
The WHERE Clause
The AND, OR, and NOT Operators
The IN Operator
The BETWEEN Operator
The LIKE Operator
The REGEXP Operator
The IS NULL Operator
The ORDER BY Operator
The LIMIT Operator
Inner Joins
Joining Across Databases
Self Joins
Joining Multiple Tables
Compound Join Conditions
Implicit Join Syntax
Outer Joins
Outer Join Between Multiple Tables
Self Outer Joins
The USING Clause
Natural Joins
Cross Joins
Unions
Column Attributes
Inserting a Single Row
Inserting Multiple Rows
Inserting Hierarchical Rows
Creating a Copy of a Table
Updating a Single Row
Updating Multiple Rows
Using Subqueries in Updates
Deleting Rows
Restoring Databases

Module 8 (16 Hours): Tableau

Introduction to Tableau
Connecting to Data Sources
Data Preparation Basics
Data Blending and Joins
Data Transformation with Tableau Prep
Basic Charts and Visualizations
Formatting Visuals
Tableau’s Show Me Feature
Advanced Charts and Visualizations
Calculated Fields and Table Calculations
Using Filters and Sets
Introduction to Tableau Maps
Advanced Mapping Techniques
Spatial Calculations and Custom Territories
Dashboard Design
Adding Interactivity
Designing Data Stories
Publishing and Sharing Dashboards
Tableau Server and Tableau Online
Exporting and Presentation
Advanced Calculations and LOD Expressions
Performance Optimization
Tableau Extensions and APIs
Case Studies
Final Project

Module 9 (8 Hours): Introduction to DATA SCIENCE FOUNDATION

Part 1: DATA SCIENCE ESSENTIALS

Introduction to Data Science
Evolution of Data Science
Big Data Vs Data Science
Data Science Terminologies
Data Science vs AI/Machine Learning
Data Science vs Analytics

Part 2: DATA SCIENCE DEMO

Business Requirement: Use Case
Data Preparation
Machine learning Model building
Prediction with ML model
Delivering Business Value.2

Part 3: ANALYTICS CLASSIFICATION

Types of Analytics
Descriptive Analytics
Diagnostic Analytics
Predictive Analytics
Prescriptive Analytics
EDA and insight gathering demo in Tableau

Part 4: DATA SCIENCE ROLES & WORKFLOW

Data Science Project workflow
Roles: Data Engineer, Data Scientist, ML Engineer and MLOps Engineer
Data Science Project stages.

Part 5: DATA SCIENCE INDUSTRY APPLICATIONS

Data Science in Finance and Banking
Data Science in Retail
Data Science in Health Care
Data Science in Logistics and Supply Chain
Data Science in the Technology Industry
Data Science in Manufacturing
Data Science in Agriculture

Module 10 (12 Hours): Advanced Statistics

Introduction to Inferential Statistics
Probability
Random variables
Probability Distribution
Empirical Rule
Convert to Standard Normal Distribution
Z Score
Using Z Table
Hypothesis Testing
Understanding P Value

Module 11 (8 Hours): Advanced Python

Functions
Classes and Objects

Module 12 (26 Hours): Machine Learning

Introduction to machine learning
Cluster Analysis
Association, correlation and covariance
Classification
Linear regression
Logistic regression
Decision Tree
Random Forest
Model evaluation
Support vector machine
Dimensionality reduction
KNN (K- Nearest neighbors)
K-means Clustering
Ensemble Learning
Optimisation

Module 13 (26 Hours): Deep Learning

Introduction to Deep Learning
Introduction to Artificial Intelligence
Introduction to Deep Learning Module
Deep Learning Model Practical with TensorFlow and Keras
Computer Vision
- Introduction to Convolutional Neural Networks
- Decoding Image Components
- Identifying MNIST using CNN
- Preprocessing Image Data to apply CNN
Natural Language Processing
- Introduction to NLP & Word Vectors
- Decoding Textual Data
- NLP using Recurrent Neural Networks (RNN)
- NLP using Memory Alterations
Framework – Apache Spark
Map and FlatMap
Transformers, Estimators, and Pipelines
Text Mining
Network Mining
Python Matrix Libraries

MODULE 14 (4 Hours): GIT & GITHUB FOR DATA SCIENCE

Part 1: Version Control

Purpose of Version Control
Popular Version control tools
Git Distribution Version Control
Terminologies
Git Workflow
Git Architecture

Part 2: GIT REPOSITORY and GitHub

Git Repo Introduction
Create New Repo with Init command
Git Essentials: Copy & User Setup
Mastering Git and GitHub

Part 3: COMMITS, PULL, FETCH AND PUSH

Code Commits
Pull, Fetch and Conflict Resolution
Pushing to Remote Repo

Part 4: TAGGING, BRANCHING AND MERGING

Organise code with branches
Checkout branch
Merge branches
Editing Commits
Commit command, Amend flag
Git reset and revert

Part 5: GIT WITH GITHUB AND BITBUCKET

Creating GitHub Account
Local and Remote Repo
Collaborating with other developers

MODULE 15 (4 Hours): ML MODEL DEPLOYMENT WITH FLASK

Introduction to Flask
URL and App routing
Flask application – ML Model deployment

Module 16 (8 Hours): Capstone Project

A comprehensive, end-to-end project to apply all course concepts.
Solves a real-world or business-simulated problem using data

Languages and Tools You will Master

Who is Eligible for Data Science Course?

Fresh Graduates- Looking for their first job in tech.
IT & Non-IT Professionals- Wanting a career switch.
Business Analysts & Statisticians- Want to enhance their skill set.
Engineers & Developers- Seeking high-paying opportunities in Artificial Intelligence/ML.

If you have a passion for data, problem-solving, and logical thinking, our Data Science course is for you!

Data Science Course Requirements

Our course is beginner-friendly and requires no programming experience. Here are a few things to have:

Why Choose PyNet Labs?

20+ industry relevant projects

Problem Solving Sessions

Instructor-Led
Live Training

Placement Assistance

Lifetime Access to training recordings

Guaranteed to Run Batches

Post-training Support

Flexible Batch-Timings

Interview Preparation

Career Counselling by Experts

On-Demand classes available

Free Demo Class

What Our Students Say About Us?

Mellissa Correia

I really admire our Network Automation Instructor Chirag's creative approach to lessons and the way he converts complex topics in a very understandable one with a relative ease, he is also very supportive....

Kumar As

It's a very good institute to learn automation. I had no experience programming, but after joining CCNA DEVNET, I am now capable of writing my own python automation scripts. I am grateful to Chirag for his patient....

Steve Kpah

I can say without mincing words that PyNet Labs is a Solid training institute for Networking and Network Automation courses.....a place where You can get the very best.

Ranjith Asam

My experience with PyNetLabs is overwhelming..!
Python Devnet course is very well structured to understand the network automation concepts.
I am new to the world of programming languages and Trainer Mr.Chirag is very helpful....

Anand Sriram

I studied a Python+Devnet automation course and i really enjoyed the session, All the sessions were really good Tutor Chirag was very good in explaining doubts and providing support when we have issues with the LAB, The phase of the course is good....

Aswathy Sreekumari

I am attending Python+ Devnet course from PyNetl Labs. Instructor Mr.Chirag is very informative and the course is well structured. The course covers from basics of python to advanced concepts of network automation. Will surely recommend this....

Abhijeet Agarwal

Python Devnet course taught by Chirag Dhall is quite an informative course . Actually all sessions were very helpful. This helped understand and streamlined the thoughts on Network Automation and Chirag is an amazing teacher, calm and composed. a rare trait.

Mansoor Ali Syed

PyNet Labs is the best place to learn Python, and we got a good instructor(Chirag Dhall)..Good Place to start the Network automation journey..!

Placement Guarantee: How It Works?

Complete the Course & Projects: Gain in-depth knowledge with hands-on practice.
Mock Interviews & Resume Building: Prepare with expert guidance.
Guaranteed Job Referrals: We connect you with hiring companies.
Land Your Dream Job: Secure a high-paying job in Data Science!

What Makes Our Data Science Course Different?

Practical, Hands-On Training: Work on real datasets and industry projects.
Career-Focused Curriculum: Learn job-relevant skills that employers look for.
100% Placement Guarantee: Secure a job in data science or get your money back.
Expert Mentors & Live Doubt Sessions: Get guidance from professionals working in top companies.
Soft Skills & Interview Preparation: Ace technical interviews with mock tests and resume-building sessions.

By the end of our Data Science Course with Placement Guarantee, you won’t just understand data science concepts—you’ll have the confidence to apply them in real-world business scenarios. Plus, with our placement guarantee, you can focus on learning while we help you land a high-paying job in data science.

Book 1:1 Free Counselling Session

Data Science Course(#113)

Name

Mobile

Country

Industry Recognized Data Science Certification

Worldwide Recognition

Get a certification that is recognized worldwide and can open doors to various new opportunities.

Lifetime Validity

Your Certification will be valid
for a lifetime.

Our Students Placed At

Alumni Highlights

Learn from Industry Experts

Abhijit Bakale

(CTO & CO-Founder at PyNet Labs)

Mr. Abhijit is the brain behind our training modules, lab setup, and course materials at PyNet Labs. He plays a big role in making sure our training is practical, updated, and easy to follow. He is a Cisco Certified Systems Instructor (CCSI #35944) and also holds the highly respected DevNet Expert certification (#20230021). In total, he has earned 14 Cisco certifications, showing just how skilled and experienced he is. Mr. Abhijit has delivered over 20,000 hours of training and has helped thousands of students grow in their careers. His deep knowledge and teaching style make learning complex topics much easier. Recently, he was invited by Cisco DevNet to speak at a live webinar on Network Services Orchestrator (NSO), which shows the high level of trust and recognition he has in the networking world. With his vast experience and passion for teaching, Mr. Abhijit continues to inspire and guide learners every day.

Chirag Dhall

(Corporate Trainer at PyNet Labs)

Mr. Chirag is a skilled and enthusiastic trainer at PyNet Labs. He has been with the company since the beginning and has played a key role in shaping many of our training programs. He delivers training for CCNA, CCNP ENCOR, CCNP ENARSI, CCIE Enterprise, Cisco SD-WAN, and other networking courses. He holds two top-level Cisco certifications—CCIE Enterprise Infrastructure (#68677) and CCSI (#36137)—which show his deep knowledge and teaching skills. So far, he has trained more than 3,500 students. Whether someone is just starting out or already working in the industry, Mr. Chirag is great at explaining tough topics in a simple and easy-to-understand way. His friendly teaching style and strong understanding of networking make him a favorite among students.

Sohel Japanwala

(Senior Technical Trainer at PyNet Labs)

Mr. Sohel is a knowledgeable and dedicated trainer at PyNet Labs, with strong expertise in both Networking and Data Science. He has trained over 1,000 students, helping them build solid skills and confidence in their careers. He delivers training on CCNA, ENCOR, ENARSI, BGP, OSPF, MPLS, CCNP SCOR, FTD, and many other networking topics. Alongside this, he also teaches Data Science and Data Analytics, making him a well-rounded trainer with a unique mix of skills. Students appreciate Mr. Sohel for his friendly and supportive teaching style. Whether someone is just starting out or already working in the field, he makes complex topics simple and easy to understand. His clear explanations and dedication to student success have earned him a strong reputation.

Sudhangshu Bag

(Corporate Trainer at PyNet Labs)

Mr. Sudhangshu Bag is a highly experienced trainer with over 9 years of expertise in the Networking field. His expertise are in CCNA, CCNP ENCOR, CCNP ENARSI, CompTIA, and Red Hat, making him a versatile and well-qualified instructor. In addition to Networking, he has strong skills in Linux, AWS, and computer networks, which add great value to his training sessions. So far, he has delivered more than 1,000 hours of training at PyNetLabs, helping students understand both the basics and advanced topics with ease. Mr. Sudhangshu is known for his calm teaching style, deep technical knowledge, and genuine passion for helping others learn. His students appreciate how he explains topics clearly and supports them throughout their learning journey.

Still have any Doubts?

Frequently Asked Questions

Q1. Is this course suitable for beginners?

Yes! Our Data Science course starts from the basics, so you don’t need prior experience. We guide you step by step from fundamental concepts to advanced topics in data science.

Q2. Do I need coding experience to join this course?

No! We teach Python programming from scratch, so even non-technical learners can master data science.

Q3. How does the placement guarantee work?

After successfully completing the course and fulfilling the eligibility criteria, we provide job referrals, mock interviews, resume building, and career guidance to help you land a job. If you don’t get placed within the guaranteed period, we offer a money-back guarantee.

Q4. What salary can I expect after this course?

Entry-level salaries for data science professionals range from INR 6 to 8 LPA, while experienced professionals can earn INR 15 to 25 LPA or more, depending on skills and expertise.

Q5. What is the duration of this course?

The course duration of our Data Science Course with Placement Guarantee is 6 Months, with flexible learning options, including weekday and weekend batches.

Q6. What tools and technologies will I learn?

You will gain hands-on experience with Excel, Python, SQL, Machine Learning, Deep Learning, Tableau, Power BI, TensorFlow, AWS, and Big Data tools used in the industry.

Q7. What kind of projects will I work on?

You will work on real-world projects across industries like finance, healthcare, e-commerce, and marketing, including predictive analytics, fraud detection, and AI-driven solutions.

Q8. Will I receive a certification after completing the course?

Yes! Upon successful completion, you will receive a globally recognized Data Science Certificate, which can boost your resume and LinkedIn profile.

Q9. What kind of job roles can I apply for after completing Data Science course?

You can apply for roles such as:

Data Scientist
Machine Learning Engineer
Data Analyst
Artificial Intelligence Engineer
Business Intelligence Analyst, etc.

Q10. How much time should I dedicate per week to complete this course?

We recommend dedicating 8-12 hours per week for best results. However, we offer flexible learning options so you can learn at your own pace.

Q11. Do you provide placement support if I already have experience in IT or analytics?

Yes! If you’re an experienced professional, we help you upgrade your skills, refine your resume, and connect with better job opportunities in data science.

Q12. What if I miss a class?

No worries! All classes of Our Data Science Course are recorded, and you’ll have lifetime access to the learning materials so you can catch up anytime.

Data Science Course with Placement Guarantee

Data Science Course Overview

Why Choose Our Data Science Course with Placement Guarantee?

Upcoming Batches

Upcoming Batches

What is Data Science?

Why You Should Learn Data Science?

Course Curriculum

Module 1 (8 Hours): Introduction to Data Analytics

Module 2 (16 Hours): Microsoft Excel

Module 3 (8 Hours): Introduction to Statistics

Module 4 (16 Hours): Introduction to Python

Module 5 (16 Hours): Analytics using Python

Module 6 (16 Hours): Power BI

Module 7 (16 Hours): SQL

Module 8 (16 Hours): Tableau

Module 9 (8 Hours): Introduction to DATA SCIENCE FOUNDATION

Module 10 (12 Hours): Advanced Statistics

Module 11 (8 Hours): Advanced Python

Module 12 (26 Hours): Machine Learning

Module 13 (26 Hours): Deep Learning

MODULE 14 (4 Hours): GIT & GITHUB FOR DATA SCIENCE

MODULE 15 (4 Hours): ML MODEL DEPLOYMENT WITH FLASK

Module 16 (8 Hours): Capstone Project

Languages and Tools You will Master

Who is Eligible for Data Science Course?

Data Science Course Requirements

Why Choose PyNet Labs?

20+ industry relevant projects

Problem Solving Sessions

Instructor-Led Live Training

Placement Assistance

Lifetime Access to training recordings

Guaranteed to Run Batches

Post-training Support

Flexible Batch-Timings

Interview Preparation

Career Counselling by Experts

On-Demand classes available

Free Demo Class

What Our Students Say About Us?

Placement Guarantee: How It Works?

What Makes Our Data Science Course Different?

Industry Recognized Data Science Certification

Our Students Placed At

Alumni Highlights

Learn from Industry Experts

Frequently Asked Questions

Q1. Is this course suitable for beginners?

Q2. Do I need coding experience to join this course?

Q3. How does the placement guarantee work?

Q4. What salary can I expect after this course?

Q5. What is the duration of this course?

Q6. What tools and technologies will I learn?

Q7. What kind of projects will I work on?

Q8. Will I receive a certification after completing the course?

Q9. What kind of job roles can I apply for after completing Data Science course?

Q10. How much time should I dedicate per week to complete this course?

Q11. Do you provide placement support if I already have experience in IT or analytics?

Q12. What if I miss a class?

Instructor-Led
Live Training