Data Science Course in Udaipur

Master the world of data with the premier Data Science course in Udaipur and fast-track your career in just a few months. Gain high-demand expertise in Python, Machine Learning, SQL, and Power BI to enter the data field with total confidence.

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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: 21 Mar, 2026

Next Batch: 21 Mar, 2026

Overview
Features
Placements
Certification
Curriculum
Projects
Reviews
FAQs

Data Science Course in Udaipur Overview

Welcome to the most comprehensive Data Science course in Udaipur, designed to equip you with the skills needed to succeed in a data-driven world. This program takes you from foundational concepts to advanced techniques, ensuring you can solve complex business problems. The global data science market is projected to reach an incredible $484.17 billion by 2029, and our training prepares you to be a part of this growth.

Our curriculum focuses on practical application, covering everything from Python programming and statistical analysis to machine learning and data visualization. Whether you are a recent graduate or a professional looking to upskill, this course is your gateway to a high-growth career. We provide the best Data Science training in Udaipur, blending expert-led instruction with hands-on projects to build your confidence and portfolio. You will learn to analyze data, build predictive models, and create insightful reports. Join us to start your journey toward becoming a certified data professional.

Why Choose Gyansetu’s Data Science Course in Udaipur?

Our commitment is to offer a learning journey that drives tangible career results, establishing us as the premier destination for Data Science training in Udaipur.

Customized Curriculum: Our syllabus is carefully crafted to align with current industry standards, covering everything from foundational Python and SQL to advanced machine learning concepts.
Expert Mentorship: Learn from seasoned professionals with over a decade of real-world experience, bringing practical insights directly to your training sessions.
Hands-On Projects: Develop a robust, job-ready portfolio by working on more than seven industry-relevant projects and case studies.
Placement Support: We offer comprehensive career services, including resume development, mock interview preparation, and connections to our exclusive network of hiring partners.
Flexible Scheduling: Select the learning format that best suits your lifestyle, with options for dynamic online classes or in-person sessions in Udaipur.
Interactive Sessions: Benefit from personalized attention and doubt-clearing sessions with mentors dedicated to fostering your growth throughout the program.
Recognized Certification: Obtain a Data Science certification in Udaipur valued by leading companies, enhancing your competitiveness in the job market.
Career Counseling: Receive one-on-one guidance to help you navigate your career path and achieve your professional goals effectively.
Alumni Network: Join a thriving community of past students, providing opportunities for networking and collaborative growth.
Affordable Tuition: Access high-quality training at competitive rates, with flexible, no-cost EMI options available to ensure financial accessibility.

Data Science Course in Udaipur

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 Udaipur

Track	Weekdays (Tue-Fri)	Weekends (Sat-Sun)	Fast Track
Course Duration	7 Months	9 Months	60 Days
Hours Per Day	2-3 Hours	3-4 Hours	6 Hours
Training Mode	Classroom/Online	Classroom/Online	Classroom/Online

Data Science Certification Course in Udaipur

Showcase your qualifications with our industry-respected certification, which confirms your capabilities and boosts your professional standing. After finishing the program, you’ll be awarded a certificate that validates your data science proficiency. You can feature this credential on your LinkedIn profile, resume, portfolio, and other social networks to highlight your achievements.

This certification provides:

Industry Acknowledgment: Our certificate is recognized by leading companies and signals your competence for data science positions.
Verifiable Credentials: Every certificate includes a special identifier, enabling potential employers to confirm its legitimacy.
Career Advancement: Leverage this certification to access better job prospects, pursue improved compensation, and accelerate your professional journey.

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Data Science Course Curriculum

Explore a comprehensive educational journey that covers every facet of the data landscape. This program blends academic principles with intensive practical application to prepare you for the demands of the modern workforce.

SQL

Gain expertise in database architecture and the art of query tuning. You will manage large-scale data sets using sophisticated operators, views, and joins to uncover the patterns driving organizational success.

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

Learn to design dynamic reports and transform raw numbers into clear, actionable stories. This module focuses on mastering DAX expressions and applying them to diverse industry scenarios for superior business intelligence.

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

Develop a deep command of Python, moving from basic syntax to specialized libraries like Pandas and NumPy. Exercises include extracting web data, investigating complex data structures, and creating automated workflows.

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

Establish a rigorous mathematical base by exploring probability theories and inferential testing. You will apply the normal distribution and various sampling methods to ensure your conclusions are scientifically sound

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

Learning in Python: Explore the frontier of artificial intelligence through supervised and unsupervised learning techniques. You will practice constructing, optimizing, and launching predictive models that solve real-world forecasting challenges.

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

Advanced Excel

Elevate your spreadsheet skills with complex logic, pivot tables, and statistical toolkits. Learn to streamline your office productivity using macros and create high-level summaries that support strategic executive decisions.

15 Module

Advanced Excel Course Curriculum

Workbook Protection & Security 7 Topics

Introduction to Excel
Password Protect a workbook/worksheet
Hiding & Unhiding Sheets
Protecting Workbook structure
Hiding sheets using VBA developer mode
Hiding Excel Functions
Locking/ Unlocking Cells

Data Types in Excel 8 Topics

Numbers
Text
Date Time
Currency
Percentage
Converting Numbers to Text
Converting Text to Numbers
Changing Date/Time formats

Scale up Speed using Short Keys 5 Topics

Working with Alt Key
Paste special
Insert Row/Column
Switch between worksheets
Navigate all excel features using Keyword

Conditional Formatting 6 Topics

Top Bottom Rules
Highlight Cell Rules
Data Bars
Color Scales
Exploring Rules Manager
Use formulas for cell formatting

Working on Data Tools 9 Topics

Text Filters
Number Filters
Sorting
Multi-level sorting
Text to Columns – Delimiters
Text to Columns – Fixed Width
Remove Duplicates
Data Validations
Grouping

Cell Referencing 3 Topics

Relative Referencing (A1)
Absolute Referencing ($A$1)
Partial Referencing ($A1) / (A$1)

Mathematical Functions 5 Topics

Sum/ Sumif/ Sumifs
Count/ Countif/ Countifs
SumProduct
Round/ Roundup/ Rounddown
Min/ Max/ Average

Logical Functions 5 Topics

If
And
Or
IsText
IsNumber

Lookup Functions 9 Topics

Vlookup
Vlookup with Match Function
Vlookup using (*) problems
Vlookup using Running Countif
Nested Vlookup
Hlookup
Index Match
Indirect
Offset

Text Functions 9 Topics

Char
Concatenate
Exact
Find/ Search
Left
Right
Proper
Mid
Upper

Date-Time Functions 5 Topics

Weekday
Weeknum
Day/ Month/ Year
Date / Time
Hour/ Minute/ Second

Array Functions 2 Topics

Learning functions with {}
Minif, Maxif, etc.

Charts 8 Topics

Line
Column
Pie
Bar
Combo Charts
Waterfall Charts
Doughnut Charts
Dynamic Charts using Pivot Slicers

Pivot Table & Charts 9 Topics

Pivot Table Fields
Filters/ Rows/ Columns/ Values
Insert Slicers
Insert Timelines
Group Selection
Changing Data Source
Report Layouts
Group Selection
Working with Multiple Tables using Relationship

Introduction to VBA programming 2 Topics

Record a Macro
Save macro sheet in .xlsm format

Industry Ready Data Science Projects

Get Real-World Experience

Customer Churn Prediction (Telecom / Banking)

Business Problem: High customer churn rates lead to significant revenue loss and increased acquisition costs. Identifying at-risk customers proactively is crucial for implementing targeted retention campaigns and maintaining market share.
Objective: Develop a predictive model to identify customers with a high likelihood of churning. This enables the business to prioritize retention efforts and deploy personalized interventions to improve customer loyalty.
Tech Stack: Python, SQL, Pandas, Scikit-learn, XGBoost

Recommendation Engine (E-commerce / OTT)

Business Problem: Users struggle to discover relevant products or content in vast catalogs, leading to low engagement and missed sales opportunities. A lack of personalization results in a generic user experience and lower conversion rates.
Objective: Build and deploy a recommendation system that delivers personalized content and product suggestions. The goal is to increase user engagement, improve conversion rates, and enhance customer satisfaction.
Tech Stack: Python, Collaborative Filtering, Content-Based Filtering, Surprise

Credit Risk & Loan Default Prediction (Banking)

Business Problem: Inaccurate assessment of credit risk exposes financial institutions to significant losses from loan defaults. Manual and outdated risk models are often inefficient and fail to capture complex default indicators.
Objective: Develop a machine learning model to accurately predict the probability of a borrower defaulting on a loan. This solution will support smarter, data-driven lending decisions and minimize financial risk.
Tech Stack: Python, Logistic Regression, Scikit-learn, Pandas, Matplotlib

Business Problem: Manually routing a high volume of support tickets is slow, error-prone, and leads to delayed resolutions. This inefficiency negatively impacts customer satisfaction and increases operational costs.
Objective: Automate the classification and routing of support tickets to the appropriate department using NLP. This system will accelerate resolution times, improve operational efficiency, and enhance the customer experience.
Tech Stack: Python, NLTK, Scikit-learn, TensorFlow, NLP

Business Problem: Financial fraud results in direct monetary losses and erodes customer trust. Traditional rule-based systems are often too slow and rigid to detect sophisticated, evolving fraud patterns in real-time.
Objective: Create a real-time fraud detection model to identify and flag suspicious transactions instantly. The model will help minimize financial losses, protect customer accounts, and maintain platform integrity.
Tech Stack: Python, Scikit-learn, TensorFlow, Keras, Anomaly Detection

Business Problem: Generic marketing campaigns fail to resonate with diverse customer segments, resulting in low engagement and wasted marketing spend. A one-size-fits-all approach misses opportunities for targeted promotions and personalization.
Objective: Use clustering algorithms to segment customers into distinct groups based on their behavior and demographics. These insights will enable the development of targeted marketing strategies that improve campaign ROI and customer loyalty.
Tech Stack: Python, Scikit-learn, K-Means Clustering, Pandas, Seaborn

Business Problem: Patient no-shows lead to significant revenue loss, underutilized resources, and disruptions in clinic scheduling. Inability to anticipate no-shows prevents proactive measures to fill empty appointment slots.
Objective: Build a predictive model to forecast the likelihood of a patient missing their appointment. This allows clinic staff to implement targeted reminders or overbooking strategies to optimize scheduling and reduce revenue loss.
Tech Stack: Python, Logistic Regression, Scikit-learn, Pandas, Tableau

420+

Hours of content

105+

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

Complete Data Science Stack

✔ Python + Statistics
✔ Machine Learning
✔ AI & Deep Learning
✔ Generative AI tools

✘ Limited syllabus
✘ No AI integration

Beginner to Advanced Roadmap

✔ Starts from basics
✔ Step-by-step learning
✔ No coding required

✘ Assume prior knowledge
✘ No clear path

Hands-On Learning

✔ 70% practical training
✔ Real datasets
✔ Case studies & projects

✘ Theory-heavy
✘ Minimal practice

Real Industry Projects

✔ Live projects
✔ Capstone projects
✔ Business problem solving

✘ Academic projects
✘ No real exposure

Machine Learning & AI Focus

✔ ML models
✔ Predictive analytics
✔ AI-based solutions

✘ Basic ML theory
✘ No real implementation

Tools & Technologies

✔ Python, Pandas, NumPy
✔ Scikit-learn
✔ Power BI / Visualization
✔ AI tools

✘ Limited tools
✘ Outdated tech

Industry Mentors

✔ Data Scientists as trainers
✔ Real-world experience
✔ Doubt support

✘ Theoretical trainers
✘ No industry exposure

Placement Support

✔ 100% assistance
✔ Resume & interview prep
✔ Hiring support

✘ No placement support

Flexible Learning

✔ Weekday / Weekend
✔ Online + Offline
✔ Fast-track option

✘ Fixed schedule

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 Udaipur

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

Delivering Training To Wedapt

Manav Rachna University

GLA University

DPGITM

GD Goenka University

FOR QUERIES, FEEDBACK OR ASSISTANCE

Have Questions? Speak to Our 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 Udaipur

Q1. Who is this Data Science course for?

This course is designed for anyone passionate about data, including recent graduates, IT professionals looking to change domains, and business or marketing professionals wanting to upgrade their skills. No prior coding experience is required, so even beginners can join.

Q2. What is the duration of the Data Science course in Udaipur?

The course takes around 4-5 months and includes intensive training, practical projects, and placement preparation, helping you kickstart your career quickly without compromising quality.

Q3. Does the course provide placement support?

Yes, we offer 100% placement assistance. Our placement cell helps with resume building, mock interviews, and connecting you to top hiring partners. We support you until you secure your first job in data science.

Freshers can expect starting salaries between ₹4 LPA to ₹8 LPA. With experience, salaries can increase significantly as data scientists are among the highest-paid professionals in tech.

Our program is competitively priced, with flexible no-cost EMI options available. Contact our admissions team for the latest fee details and payment plans.

Absolutely. The course emphasizes learning by doing, with over seven real-world projects and case studies. You’ll gain practical experience using tools and building models throughout the training.

Yes, we offer free demo classes to help you experience our teaching style and understand the course structure. It’s a great way to see if the program aligns with your goals.

Gyansetu stands out for its expert trainers, job-focused curriculum, guaranteed internship, and dedicated placement support. We emphasize practical skills and a student-first approach, ensuring you’re industry-ready.

Yes, upon completing the course, you will earn an industry-recognized Data Science certification. This certification validates your skills and enhances your job prospects.

There are no strict prerequisites. A basic understanding of mathematics and logical thinking is helpful but not necessary. The course starts from the fundamentals, making it accessible for those from non-technical backgrounds.

You’ll work with essential tools like Python (Pandas, NumPy, Scikit-learn), SQL, Power BI, Tableau, and Advanced Excel. These tools are integral to building your data science skills.

Yes, Udaipur’s growing tech ecosystem offers increasing opportunities in IT, retail, and finance. Our placement support connects you to roles in Udaipur and major IT hubs across India.

You’ll get access to recordings of all live sessions to catch up at your convenience. Additionally, regular doubt-clearing sessions ensure you stay on track.

Yes, having your own laptop is essential for practice and project work. We’ll guide you through installing the necessary tools and software.

Unlike pre-recorded courses, this program offers live, interactive sessions with industry experts, practical projects, a guaranteed internship, and personalized placement support. It’s a complete learning and career transformation experience.

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Data Science Course in Udaipur

Data Science Course in Udaipur Overview

Why Choose Gyansetu’s Data Science Course in Udaipur?

Key Highlights of Data Science Course

Placement Stats

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Data Science Course Placement Highlights

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Data Science Certification Course in Udaipur

Data Science Course Curriculum

SQL

Power BI

Python for Data Science

Statistics for Data Science

Machine Learning in Python

Advanced Excel

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 Udaipur

Top Companies Hiring for Data Science Role

Honours & Awards Recognition

Our Learners Testimonials

FAQ: Data Science Course in Udaipur

Q1. Who is this Data Science course for?

Q2. What is the duration of the Data Science course in Udaipur?

Q3. Does the course provide placement support?

Q4. What is the starting salary after completing the course?

Q5. How much does the Data Science course in Udaipur cost?

Q6. Is this course hands-on and practical?

Q7. Can I attend a demo class before enrolling?

Q8. Why is Gyansetu the best institute for Data Science in Udaipur?

Q9. Will I receive a recognized certification?

Q10. Are there any prerequisites for joining the course?

Q11. What tools and technologies will I learn?

Q12. Are there job opportunities for data scientists in Udaipur?

Q13. What happens if I miss a class?

Q14.Do I need a laptop for the course?

Q15: How is this course different from other online programs?