Data Science Course in Patna

Our Patna campus has a Data Science Programme that offers a systematic avenue of students who would like to further their career life. Participants become proficient in Python, machine learning, SQL, and Power BI by working on applied projects. The local market, which is represented by a small number of major companies, is actively interested in finding qualified data scientists to fill high-paid analytics and artificial-intelligence positions.

4.8 (8976 Reviews)

4.8

4.7

5.0

Job Guarantee Program 100% Support Until You’re Hired

Course Duration 6 Months + Life Time Access

Expert Mentorship Learn from Industry Experts

Flexible Learning Available in Classroom/Online formats

Next Batch: 27 Dec, 2025

Next Batch: 27 Dec, 2025

Overview
Features
Placements
Certification
Curriculum
Projects
Reviews
FAQs

Data Science Course in Patna Overview

To the individuals who are wishing to have a high-paying career in the field of analytics, the curriculum is recommended to instill the most desired data skills, thus making it easy to enter into the growing field of AI and analytics.

The programme combines real-time learning with experienced professionals as well as project-based learning. This integration provides the participants with real-life experience with the help of such tools as Python, SQL, Power BI, and modern machine-learning algorithms. Both undergraduate and graduate students will be using real data sets, learning how to clean, analyze, and visualize data to provide actionable business information.

The course provides recent graduates, IT professionals who need to improve their skills, and career changers with the skills necessary to be successful in a rapidly changing environment where Patna is quickly becoming an IT services, fintech, and data-focused business hub. In turn it has increased the need of skilled experts in data.

At the end of the programme, the students will be equipped with high-level technical skills, practical exposure to projects, and the confidence to work in the role of Data Scientist, Business Analyst, or even Machine-Learning Engineer in leading organisations.

Data Science Training in Patna

Key Highlights of Data Science Course

100% Placement Support

Unlimited Course Repeats

Mock Interviews

1:1 Doubt Sessions

Flexible Timing

Real Industry Projects

Placement Stats

Maximum salary hike

135%

Average salary hike

75%

Our Data Science Alumni in Top Companies

Data Science Course Placement Highlights

Shefali Agarwal

80 % Hike

Lead Analyst

Evalueserve

Analytics Specialist

Accenture

Ankit

100 % Hike

MCA

Fresher

Associate Consultant

Ernst & Young

Batches Timing for Data Science Course in Patna

Track	Weekdays (Tue-Fri)	Weekends (Sat-Sun)	Fast Track
Course Duration	5 Months	6 Months	45 Days
Hours Per Day	2-3 Hours	3-4 Hours	6 Hours
Training Mode	Classroom/Online	Classroom/Online	Classroom/Online

Data Science Certification in Patna

The completion of the Data Science Programme makes a certificate that is recognized throughout the industry, thus raising the professional standing of a person and his or her chances of getting a job in one of the leading analytics and IT companies. Market research proves that certified practitioners are paid up to twenty percent higher than non-certified ones.

The qualification certifies data analytics and machine-learning and AI-based problem-solving skills and prepares candidates to work in the business intelligence, predictive modelling, and advanced analytics fields. With the help of presenting this certification on professional platforms like LinkedIn, the recruiters of the top IT companies, fintech startups, and consulting agencies in Patna will be more inclined to identify and hire the person. Most of the holders of this certificate later on get better-paying jobs and senior jobs, a fact that supports the usefulness of the certificate as a strategic career investment.

Enrollment is thus not just an academic endeavor but a calculated move towards the long-term career improvement in the tech and analytics ecosystem that is currently booming in Patna.

Enquire Now

Data Science Course Curriculum

Gyansetu's data science course in Patna is designed in such a way that they get to master job ready skills, Python, SQL, Power BI and machine learning. These skills help you to get high-paying jobs in Patna.

SQL

SQL helps to handle and process large volumes of data effectively. This is essential for formulating queries, creating powerful reports and optimising the database performance. These are the essential competencies in the sectors such as IT services, banking and manufacturing in Patna.

13 Modules

SQL Certification Course

Introduction 5 Topics

File Management System and Its Drawbacks
Overview of Database Management System (DBMS) and Data Models
Physical Data Models
Logical Data Models
Entity-Relationship (E-R) Model

Introduction to Sql Server 10 Topics

Advantages and Drawbacks of SQL Server Compared to Oracle and DB2
Connecting to Server
Authentication Modes
SQL Server Authentication Mode
Windows Authentication Mode
Login and Password
SQL Server Management Studio and Tools in Management Studio
Object Explorer
Object Explorer Details
Query Editor

Introduction to tsql 19 Topics

Types Of TSQL Commands
Data Definition Language (DDL)
Data Manipulation Language (DML)
Data Query Language (DQL)
Data Control Language (DCL)
Transaction Control Language (TCL)
Database
Creating Database
Altering Database
Deleting Database
Constrains
Procedural Integrity Constraints
Declarative Integrity Constraints
Not Null, Unique, Default and Check constraints
Primary Key and Referential Integrity or foreign key constraints
Data Types In TSQL
Table
Creating Table
Altering/ Deleting Table

Data Manipulation Language 9 Topics

Insert
Identity
Creating A Table From Another Table
Inserting Rows From One Table To Another
Update
Computed Columns
Delete
Truncate
Difference Between Delete and Truncate

Data Query Language (DQL) 12 Topics

Select Clause
Where clause
Top clause
Order By Clause
Distinct Clause
Isnull() function
Column aliases
Predicates
Between … And
In
Like
Is Null

Built In Functions 13 Topics

Scalar Functions
Numeric Functions
Character Functions
Conversion Functions
Date Functions
Aggregate Functions
Convenient Aggregate Functions
Statistical Aggregate Functions
Group By and Having Clauses
Super Aggregates
Over (partition by …) Clause
Ranking Functions
Common Table Expressions (CTE)

Set Operators 3 Topics

Union
Intersect
Except

Joins 9 Topics

Inner Join
Equi Join
Non-Equi Join
Self-Join
Outer Join
Left Outer Join
Right Outer Join
Full Outer Join
Cross Join

Sub Queries 7 Topics

Single Row Sub Queries
Multi Row Sub Queries
Any or Some
ALL
Nested Sub Queries
Co-Related Sub Queries
Exists and Not Exists

Indexes 4 Topics

Clustered Index
Non-Clustered Index
Create, Alter and Drop Indexes
Using Indexes

Security 4 Topics

Login Creation
User Creation
Granting Permissions
Revoking Permissions

Views 3 Topics

Purpose Of Views
Creating, Altering and Dropping Indexes
Simple and Complex Views

Transaction Management 4 Topics

Introduction
Begin Transaction
Commit Transaction
Rollback Transaction

Power BI

By using Power BI, students will gain the necessary competency to build interactive dashboards and analysis reports. They will bring these competencies to case studies in the real world in areas like healthcare, retail and manufacturing, and thus turn raw data into actionable information that data-driven organisations are taking action on.

12 Modules

Power BI Certification Course Curriculum

Introduction 7 Topics

Power BI Installation
Power BI Desktop
Data Imports into Power BI
Views in Power BI
Building a Dashboard
Publishing Reports
Creating Dashboard in Power BI

Components 8 Topics

Power Query
Power Pivot
Power View
Power Map
Power BI Service
Power BI & QA
Data Management Gateway
Data Catalog

Integration with Data Sources 8 Topics

Connect to DataSources
Power BI SQL Server Integration
Power BI MySQL Integration
Power BI Excel Integration
Python Integration with Power BI Desktop
Power BI Web Integration using APIs
Power BI Salesforce Integration
Power BI Microsoft Integration

Power Query Editor 14 Topics

Change Data type of column
Clean and Transform using Query Editor
Advanced Data sources and transformations
Cleaning irregularly formatted data
Combine Multiple tables
Clusters
Format dates
Groups
Hierarchies
Joins
Pivot table
Query Groups
Split Columns
Unpivot table

Data Models/ Relationship 14 Topics

How Data Model Looks Like
Database Normalization
Data Tables vs Lookup Tables
Primary Key vs Foreign Key
Relationships vs Merged Table
Creating Table Relationships
Creating Snowflake Schemas
Managing & Editing Relationships
Active vs Inactive Relationships
Relationship Cardinality
Many to Many
One to One
Connecting Multiple Data Tables
Filter Flow

Data Analysis Expressions (Dax) Functions 7 Topics

Introduction to DAX
DAX calculation types
Aggregate Functions
Date Functions
Logical Functions
String Functions
Trigonometric Functions

Charts 21 Topics

Area Chart
Bar chart
Card
Clustered Bar chart
Clustered Column chart
Donut chart
Funnel chart
Heat Map
Line Chart
Clustered Column and Line chart
Line and Stacked Column chart
Matrix
Multi-Row Card
Pie chart
Ribbon chart
Stacked Area char
Scatter Chart
Stacked Bar chart
Waterfall chart
Map
Filled Map

Filters 8 Topics

Slicer Basic
Filters
Advanced Filters
Top N Filters
Filters on Measures
Page Level Filters
Report Level Filters
Drill through Filters

Visualizations 12 Topics

Visuals in Power BI
Create and Customize simple visualizations
Combination charts
Slicers
Map visualizations
Matrixes and tables
Scatter charts
Waterfall and funnel charts
Gauges and single-number cards
Modify colors in charts and visuals
Z-Order
Duplicate a report page

Exploring Data 5 Topics

Power BI Service
QuickSights in Power BI
Create and configure a dashboard
Share dashboards with organizations
Install and configure personal gateway

Power BI and Excel 4 Topics

Using Excel Data in Power BI
Upload Excel Data to Power BI
Import Power View and Power Pivot to Power BI
Connect OneDrive for Business to Power BI

Power BI Publishing and Sharing 11 Topics

Introduction to content packs, security and groups
Publish Power BI Desktop reports
Print and export dashboards and reports
Manually republish and refresh your data
Introduction Power BI Mobile
Creating groups in Power BI
Build content packs
Use content packs
Update content packs
Integrate OneDrive for Business with Power BI
Publish to web

Python for Data Science

The Python training will include data cleaning, data analysis and automation. The participants will work with libraries such as NumPy, Pandas, and Matplotlib and will perform exploratory data analysis and hypothesis testing to answer the business questions about demand forecasting and process optimisation.

12 Modules

Python for Data Science Certification Curriculum

Introduction 6 Topics

Interpreted vs Compiled language
Introduction to Python
Advantages & Disadvantages of Python
Python Installation (Anaconda)
Applications of Python
“Hello World!” in Python

The Basics (DataTypes) 17 Topics

Variables
Keywords
Multiple Assignment
What are Datatypes?
Numbers
Strings
Indexing and Slicing
String Functions
Lists
List Functions
Dictionary
Dictionary Functions
Tuples
Sets
Type Conversion (Str, Int, Float, etc.)
Date & Time (Date, Time and DateTime classes in Python)
Operators (Arithmetic, Comparison, Logical, Assignment, Binary, Identity, Membership Operators)

Conditional Statements & Loops 9 Topics

If-Else statements
Relational Operators
Nested If/Else
Elif Statements
Logical Operators
For Loops
While Loops
Nested Loops
Pass, Break and Continue

Functions 7 Topics

User-defined functions
Unlimited parameters
Global and Local variables
Lambda functions
Map function
Sort function
Error and Exception Handling

Python Comprehensions 4 Topics

List Comprehensions
Dictionary Comprehensions
Set Comprehensions
Tuple Comprehensions (doesn’t exist)

Oops 6 Topics

Classes and Objects
Methods in Classes
Class Attributes
Instance Attributes
Inheritance
Overriding Methods

File Handling 5 Topics

Creating a file
Reading a file
Writing a file
Appending to file
Copying file

Web Scraping 7 Topics

Intro to requests
Intro to BeautifulSoup
Parsing HTML structure into soup
Data extraction from soup/HTML
Wikipedia scraping
News website scraping
Maps scraping

Database Integration 6 Topics

What is a database?
What is SQL (Structure Query Language)?
Introduction to MySQL
Installing MySQL
Connection MySQL with Python
CRUD operations

Multi-Threading 7 Topics

What is multi-threading?
Introduction to parallel processing
Intro to threads
Threading module
Creating threads using threading module
Synchronizing threads
Threads priority queue

Exploratory Data Analysis 4 Topics

Working with NumPy
Working with Pandas
DataFrames
Analyzing a dataset using NumPy and pandas

Natural Language Processing (NLP) 12 Topics

Intro to Natural Language Processing
Installing NLTK toolkit
Working with NLTK Toolkit
Sentence Segmentation
Word Tokenization
Parts-of-Speech Tagging
Lemmatization
Stop-word removal
Named Entity Recognition (NER)
Bag of words model
TF-IDF (Term Frequency – Inverse Document Frequency)
ML modelling

Statistics for Data Science

Strict treatment of probability, hypothesis testing, sampling, and statistical modelling offer students the analytical basis to make correct predictive modelling and process improvement in finance and IT applications throughout Patna.

4 Modules

Statistics for Data Science Course Curriculum

Descriptive Statistics 5 Topics

Intro to Descriptive Statistics
Measures of Center: Average, Mean, Median, Mode
Measures of Dispersion: Range, Quartiles and Percentiles, Inter Quartile Range (IQR), Variance, Standard Deviation
Covariance and Correlation
Simpson’s Paradox

Inferential Statistics 8 Topics

Normal Distribution
Standard Normal Distribution
T- Distribution
Point Estimation
Confidence Intervals
P-Value
Hypothesis testing
Levels of Hypothesis Testing

Probability 7 Topics

Uses of Probability
Need of Probability
Basics of Probability
Binomial Distribution
Conditional Probability
Bayesian Inference
Bayes Rule

Regression Modelling 7 Topics

Linear Regression Analysis
Logistic Regression Analysis
Problem of Collinearity
WOE and IV
Residual Analysis
Heteroscedasticity
Homoscedasticity

Machine Learning in Python

Students here will participate in live projects, which will help them to gain skills which are required for data science jobs within Patna.

12 Modules

Machine Learning in Python Course Curriculum

Introduction to Machine Learning with Python 6 Topics

Python Revision (NumPy, Pandas, scikit learn, matplotlib)

What is Machine Learning?
Statistical Learning vs Machine Learning
Machine Learning Use-Cases
Machine Learning Process Flow
Machine Learning Categories

Model Evaluation Metrics 11 Topics

Accuracy
Precision
Recall
True Positive Rate / False Positive Rate
F1-Score
Confusion Matrix
ROC Curve
Area Under the ROC curve
Mean Absolute Error (MAE)
Mean Squared Error (MSE)
R2 Score

Supervised Learning – Regression 5 Topics

What is Regression and its use cases?
Linear Regression
Polynomial Regression
Support Vector Regression (SVR)
Decision Tree Regression – ID3 and CART

Supervised Learning – Classification 11 Topics

What is Classification and its use cases?
Logistic Regression
Support Vector Machine (SVM)
Kernel SVM
Naïve Bayes
k-Nearest Neighbours (k-NN)
Decision Tree Classification – ID3 and CART Algorithms
Ensemble Learning
Bagging vs Boosting
AdaBoost, Gradient Boost, XGBoost
Random Forest

Hyperparameter Tuning 6 Topics

What is model tuning?
Overfitting vs Underfitting
Cross Validation
Bias and Variance
Hyperparameter Optimization
Grid Search vs Random Search

Dimensionality Reduction 6 Topics

What is Dimensionality Reduction?
Feature Selection
Principal Component Analysis (PCA)
Linear Discriminant Analysis (LDA)
Random Projection
ICA

Unsupervised Learning 9 Topics

What is Clustering & its Use Cases?
K-Means Clustering
K-Means++
How to do optimal clustering – Elbow Curve?
C-means Clustering
Hierarchical Clustering
DBSCAN Clustering
Gaussian Mixture Model
Clustering Model Evaluation Metrics – Silhouette Coefficient, Dunn’s Index, etc.

Association Rules Mining and Recommendation Systems 7 Topics

What are Association Rules?
Association Rule Parameters
Calculating Association Rule Parameters
Recommendation Engines
How Recommendation Engines work?
Collaborative Filtering
Content Based Filtering

Reinforcement Learning 9 Topics

What is Reinforcement Learning?
Why Reinforcement Learning?
Elements of Reinforcement Learning
Exploration vs. Exploitation dilemma
Epsilon Greedy Algorithm
Markov Decision Process (MDP)
Q values and V values
Q – Learning
Values

Time Series Analysis 8 Topics

What is Time Series Analysis?
Importance and Components of TSA
White Noise
AR model
MA model
ARMA model
ARIMA model
Stationarity

Natural Language Processing (NLP) 18 Topics

Intro to NLP
Setting up NLTK environment
What is NLTK Toolkit?
Text Processing
- Cleaning
- Normalization
- Tokenization
- Stop Word Removal
- Part of Speech Tagging
- Named Entity Recognition
- Stemming
- Lemmatization
Feature Extraction
- Bag of Words Model
- Count Vectorizer
- Term Frequency (TF)
Inverse Document Frequency (IDF)
- Word Embeddings

Introduction to Deep Learning 11 Topics

What is Deep Learning?
Curse of Dimensionality
Machine Learning vs. Deep Learning
Use cases of Deep Learning
Human Brain vs. Neural Network
What is Perceptron?
Learning Rate
Epoch
Batch Size
Activation Function
Single Layer Perceptron

Industry Ready Data Science Projects

Get Real-World Experience

Health Monitoring and Disease Prediction

You will be working on decision trees, neural networks, support vector machines to predict diseases and monitor health. The input data like vital signs, medical history, and diagnostic results will be gathered in a pre-processed manner to predict disease probability, personalized health insights, and early warnings.

Credit Risk Assessment

You will be working on Machine learning algorithms like Random Forest, Gradient Boosting, and Logistic Regression to predict the default applications. You will be developing a prediction model to check credit risks for loan applications by examining credit scores, personal data and repayment patterns of the customer.

480+

Hours of content

120+

Live sessions

Tools and software

Data Science Skills you can add in your CV

Data Science Tools Covered

What Sets This Program Apart?

GyanSetu

Other Courses

all-in-oneAll-in-One Toolkit

Complete roadmap: Gen AI, Python, Machine Learning, Deep Learning, Statistics, Power BI, SQL

Limited topics, outdated tools, no Generative AI or ML coverage.

progress-iconBeginner-to-Pro

Starts from scratch, no prior knowledge required, progressive skill-building.

Assume prior knowledge, leaving beginners confused and lost.

empoweredAI-Integrated Learning

Modern Data Science powered with Gen AI tools like ChatGPT, Gemini, Copilot, Midjourney & LLMs in every module.

No exposure to modern AI tools, LLMs, or data-driven automation.

focusedCareer-Focused Tracks

Choose your specialization – ✔ Data Scientist ✔ Machine Learning Engineer ✔ AI Engineer ✔ Data Analyst (bridge track included)

One-size-fits-all curriculum with zero career customization.

Real Industry Exposure

25+ hands-on industry projects + 2 live capstone projects using real company datasets.

Only 1–2 academic or theoretical projects with no real-world application.

expertiseLegacy & Expertise

Founded by IIIT-H alumni with 15+ years of tech, AI & training expertise.

Trainers with limited real-world data science or AI background.

practicePractice Over Theory

70% hands-on coding with ML models, datasets, AI pipelines & real problem-solving.

Primarily theory-based learning with limited practical implementation.

mentorshipExpert Mentorship

Learn directly from working Data Scientists & ML Engineers from Amazon, Deloitte, Accenture & top AI teams.

Generic trainers with no active industry involvement.

Who is this course for?

Aspiring Data Scientists/ AI Professionals
Software Engineers
Data Analysts
Career Changers
Statisticians
Academic Researchers and Educators

Career Assistance for Data Science Course in Patna

Job Opportunities Guaranteed

Get a 100% Guaranteed Interview Opportunities Post Completion of the training.

Access to Job Application & Alumni Network

Get chance to connect with Hiring partners from top startups and product-based companies.

Mock Interview Session

Get One-On-One Mock Interview Session with our Experts. They will provide continuous feedback and improvement plan until you get a job in industry.

Live Interactive Sessions

Live interactive sessions with industry experts to gain knowledge on the skills expected by companies. Solve practice sheets on interview questions to help crack interviews.

Career Oriented Sessions

Personalized career focused sessions to guide on current interview trends, personality development, soft skill and HR related questions.

Resume & Naukri Profile Building

Get help in creating resume & Naukri Profile from our placement team and learn how to grab attention of HR’s for shortlisting your profile.

Top Companies Hiring for Data Science Role

Honours & Awards Recognition

GD Goenka University

Livpure

Denso International

ReverseLogix

BML Munjal University

Manav Rachna University

GLA University

DPGITM

GD Goenka University

FOR QUERIES, FEEDBACK OR ASSISTANCE

Have Questions? Speak to Our Lucknow Experts!

+91 9999 201 478 +919999201478

4.8

4.7

5.0

Our Learners Testimonials

Pawan Kumar

I joined Gyansetu institute for Data Science, faculty is brilliant here. Training got completed in around 6 months.

Shruti Aggarwal

Gyansetu's practical learning methodologies have been invaluable. Institute focuses on hands-on projects and industry-relevant curriculum equipped me with the skills needed to analyze complex datasets and derive actionable insights for my organization.

Divya Singh

I was passionate about data analysis it was an amazing experience learning Data Analytics from Gyansetu. Here the faculties helped me learn from the basics to advanced concepts and with the practice on real projects I was able to crack the job.

Self Assessment Test

Learn, Grow & Test your skill with Online Assessment Exam to achieve your Certification Goals.

FAQ: Data Science Course in Patna

Which course is best for data science?

Gyansetu’s data science course in Patna helps you to cover important topics like Python, SQL, Power BI and machine learning. This way, you can build a strong foundation and a practical portfolio that meets the needs of today’s recruiters.

Who is eligible for data science?

Anyone can apply. This course has an open admissions policy. Anyone can apply, including recent grads, experienced IT workers, engineers, and people with no technical background. To enroll in this course, it is not necessarily important that you have coding experience. The main thing that is required is skills.

Is data science hard?

At first, data science may seem hard, but with the right step-by-step and project-based teaching methods, it can be learned by anyone, even those who have never worked with technology before. Gyansetu’s method focuses on learning by doing, breaking down difficult ideas through hands-on tasks and real-world examples so that even beginners can understand and master the material.

Yes, working as a data scientist pays well. Data scientists are always among the highest-paid analytics professionals. This means that salaries are higher than average and long-term job prospects are good.

After finishing your course with Gyansetu, you will get a certificate that is valued by most of the top industries. The certification which you get here will help you to get high-paying jobs.

No, all you need is to have the basics of coding. Our course is designed in a way that even beginners can learn technical skills faster.

The course will teach you a set of useful technologies, such as Python for automating and analyzing data, SQL for working with databases more efficiently, Power BI for business intelligence and interactive dashboards, and the latest machine learning and predictive analytics techniques. These tools are the most in-demand skills by employers in Patna and will give you a strong base for moving up in your analytics career.

frequently asked questions by students for courses

Find Data Science Course in other cities

Data Science Course in Patna

Data Science Course in Patna Overview

Key Highlights of Data Science Course

Placement Stats

Our Data Science Alumni in Top Companies

Data Science Course Placement Highlights

Batches Timing for Data Science Course in Patna

Data Science Certification in Patna

Data Science Course Curriculum

SQL

Power BI

Python for Data Science

Statistics for Data Science

Machine Learning in Python

Industry Ready Data Science Projects

Data Science Skills you can add in your CV

Data Science Tools Covered

What Sets This Program Apart?

Career Assistance for Data Science Course in Patna

Top Companies Hiring for Data Science Role

Honours & Awards Recognition

Our Learners Testimonials

FAQ: Data Science Course in Patna

Which course is best for data science?

Who is eligible for data science?

Is data science hard?

Is data science good money?

What certification will I get after completing this course?

Do I need coding experience to join this course?

What tools and technologies will I learn in this course?

Data Science Course in Patna

Data Science Course in Patna Overview

Key Highlights of Data Science Course

Placement Stats

Our Data Science Alumni in Top Companies

Data Science Course Placement Highlights

Batches Timing for Data Science Course in Patna

Data Science Certification in Patna

Data Science Course Curriculum

SQL

Power BI

Python for Data Science

Statistics for Data Science

Machine Learning in Python

Industry Ready Data Science Projects

Data Science Skills you can add in your CV

Data Science Tools Covered

What Sets This Program Apart?

Career Assistance for Data Science Course in Patna

Top Companies Hiring for Data Science Role

Honours & Awards Recognition

Our Learners Testimonials

FAQ: Data Science Course in Patna

Which course is best for data science?

Who is eligible for data science?

Is data science hard?

Is data science good money?

What certification will I get after completing this course?

Do I need coding experience to join this course?

What tools and technologies will I learn in this course?

Similar Courses we offer