Data Science Course in Noida

Enroll in a Data Science Course in Noida and master in-demand skills including Python, SQL, Machine Learning and AI. Join our expert led training with guaranteed placement support and become job-ready in just months!

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4.8

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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: 8 Aug, 2026

Overview
Features
Placements
Certification
Curriculum
Projects
Reviews
FAQs

Data Science Course in Noida Overview

Are you willing to accelerate your career in one of the highly demanded in the world? Gyansetu’s Data Science Course in Noida will be your key to a future-proof career. We are not just another training – our course provides on-the-job, practical training in Python, SQL, Power BI, Machine Learning, and Advanced Excel that allow you to be exposed to high impact business problems on the first day.

As India is expected to create 7 million data-related jobs by 2025 (NASSCOM), the demand is not high only, it is necessary to have talented data experts. That is the reason why we model our course around real-life projects such as customer churn analysis, fraud detection, and recommendation engines, making sure that you are coming out with a portfolio that is attractive to the leading employers.

Gyansetu is different with its flexible learning (online, offline, weekends), unlimited access to industry experts, and a full-time placement team that helps you get in direct contact with employment partners such as HCL, TCS, Infosys among many others. Our graduates bring on board fulfilling careers in IT, finance, healthcare, e-commerce, and consulting with an annual average starting salary of 8-20 LPA.

Read about success, but do not wait until you take the first step! Register your free demo session with us today and watch how Gyansetu will change your future with data science.

Why Choose Gyansetu’s Data Science Course In Noida?

We offer Data Science education with industry-oriented training in Noida, placement, and hands-on learning, which ensures that you are ready to achieve instant success in the competitive job market.

1. Mentors in the Industry: Obtain firsthand expertise of the most experienced experts who have more than 10 years of experience in the field.
2. Exclusive Placement Guidance: Advantage of 100 percent placement guidance, which links you with recruitment managers in top technology firms and MNCs.
3. Project-Based Learning: Develop a strong portfolio of 7+ operational projects in high-need industries of healthcare, banking and e-commerce.
4. Flexible Learning: Customize your schedule with online, offline or weekend batches.
5. Complete Stack: Become a full stack specialist – Python and SQL to Power BI, ML and Advanced Excel.
6. Small Batches, Big Results: Small Classes to Get the one-on-one attention you need in a small class that is built to be mentored and doubts cleared.
7. LMS Lifetime Access: You will always continue to learn with unlimited access to our recordings of our lectures and assignments along with new training resources.
8. Career Readiness Program: Work on your professional image through professional simulation interviews and resume-building.
9. International Certification: Gain a high-quality, globally acknowledged qualification that demonstrates your technical expertise to the employer.
10. Affordable Plans: Get high-quality education at a modest fee system and wide-ranging EMI payments.

data-science-course-in-noida

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

190%

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 Noida

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 Course in Noida

After passing the certification course in Data Science in Noida successfully, you will get an industry-accepted certificate that will confirm your mastery of Python, Machine Learning, SQL, Power BI, and Statistics. You can post this certificate on LinkedIn, your resume, and your portfolio to demonstrate your skills to the recruiters.

There are three certification advantages:

Industry Recognition: Our certification is appreciated by the leading employers in the IT, finance, healthcare, and e-commerce sectors.
Verifiable and Authentic: Each certificate has individual credentials, which make it authentic.
Career Impact: Certified professionals have better rates of higher pay, promotions and better rates of short listing in the interview.

Data Science Course Curriculum

Our Data Science certification course in Noida features a meticulously designed curriculum that covers fundamental to advanced concepts with hands-on, industry-relevant training methods, ensuring complete job readiness.

SQL

Master database management through SQL operators, functions, subqueries, views, joins, and advanced query optimization techniques. Learn to efficiently retrieve, manipulate, and analyze data from relational databases.

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

Interactive Data Visualization, Create stunning interactive dashboards and compelling data visualizations using Power BI. Master DAX functions, data modeling, and real-world case studies that transform raw data into actionable business insights.

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

Programming Fundamentals, Build strong Python programming fundamentals including web scraping, NumPy arrays, Pandas dataframes, data exploration techniques, and automation scripts. Python is the #1 language for data science professionals.

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

Mathematical Foundation, Understand probability distributions, descriptive statistics, hypothesis testing, sampling techniques, and statistical inference. These mathematical foundations are essential for building accurate predictive models.

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

AI & Model Building, Explore supervised and unsupervised learning algorithms, model building workflows, and deployment strategies. Learn to implement classification, regression, clustering, and deep learning models to solve real business 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

Business Analytics & Reporting, Master advanced formulas, pivot tables, data analysis tools, macros, and professional business reporting techniques. Excel remains indispensable for quick analysis and financial modeling.

15 Modules

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 attrition rates are leading to significant revenue loss and increased customer acquisition costs. Identifying dissatisfied customers before they leave is essential for maintaining a stable market share.

Objective: Develop a predictive model to identify high-risk customers, allowing the retention team to execute proactive and targeted outreach strategies.

Tech Stack: Python, pandas, scikit-learn, XGBoost, Matplotlib.

Recommendation Engine (E-commerce/OTT)

Business Problem: Users often struggle to find relevant content or products amidst massive inventories, leading to low engagement and lost sales opportunities. Personalized experiences are critical for driving repeat visits.

Objective: Build a recommendation system that suggests products or content based on user behavior to increase conversion rates and average session duration.

Tech Stack: Python, SQL, Surprise library, scikit-learn, NumPy.

Credit Risk & Loan Default Prediction (Banking)

Business Problem: Lending to high-risk applicants leads to increased non-performing assets and financial instability. The bank needs a reliable way to differentiate between creditworthy individuals and potential defaulters.

Objective: Develop a risk assessment model to predict the probability of loan default, enabling more informed and automated lending decisions.

Tech Stack: Python, SQL, scikit-learn, Random Forest, Seaborn.

Business Problem: Manually sorting through thousands of customer support tickets is slow, prone to error, and delays resolution times. This inefficiency leads to poor customer satisfaction and high operational costs.

Objective: Automate ticket categorization using Natural Language Processing to ensure faster routing to the correct department and quicker issue resolution.

Tech Stack: Python, NLTK, Spacy, scikit-learn, TF-IDF.

Business Problem: Fraudulent transactions result in direct financial losses and erode customer trust in digital payment systems. Detecting these anomalies manually in real-time is impossible.

Objective: Build a real-time detection model to flag suspicious transactions, minimizing financial losses and protecting the integrity of the payment platform.

Tech Stack: Python, scikit-learn, Isolation Forest, SMOTE, pandas.

Business Problem: One-size-fits-all marketing campaigns are often inefficient and result in low engagement. Businesses need to understand the unique behaviors and needs of different customer groups to optimize spend.

Objective: Apply clustering techniques to segment the customer base, allowing marketing teams to design highly targeted and effective promotional campaigns.

Tech Stack: Python, scikit-learn, K-Means Clustering, PCA, Matplotlib.

Business Problem: Missed medical appointments lead to underutilized resources, disrupted schedules, and significant revenue loss for healthcare providers. It also delays care for other patients in need.

Objective: Predict the likelihood of a patient missing an appointment to optimize scheduling, send targeted reminders, and reduce the overall no-show rate.

Tech Stack: Python, pandas, Logistic Regression, scikit-learn, Tableau.

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 los

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 Noida

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

Denso International

Luminous

Bharat Petroleum

Toshiba Midea

BryAir

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 Noida 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.

Frequently Asked Questions

Q1. What is Data Science and why is it significant?

Data Science is an interdisciplinary field that involves statistics, computer programs, and knowledge of the domain to find insights in the data. This is important since companies are guided by facts and figures to maximize operations, forecast trends, and improve customer experiences. As the market of data science in India is developing with the CAGR of 26.9 per cent, there is a high demand in professional development.

Q2. Which Data Science institutions are the top in Noida?

Faculty experience, curriculum, projects, and placement support are some of the factors to consider when selecting an institute. We also provide trainers who have over 10 years experience, 7 real-life projects, place guaranteed assistance, and also flexible modes of learning, with alumni in leading firms such as HCL, TCS, and Infosys.

Q3. What is the cost of a Data Science course at Noida?

Noida course fees are variable between 20000 and 120000. Our prices are competitive and affordable and we also have flexible EMI schemes to enable us to make quality education affordable. Our all-inclusive offer provides great value and good investment on your career.

Our course takes a duration of 3-6 months, and this will be based on the type of batches you want, like regular weekdays, weekend working and fast-track programs. All formats embrace the entire curriculum. We also offer lifetime access to recorded lectures and material to engage in lifelong learning.

There is no previous programming experience needed. We begin with the basics of Python and move on to the more sophisticated. Our courses will suit fresh graduates and non-technical professionals as well and the trainers will focus on them individually to develop robust background skills.

You may get such positions as Data Scientist, Data Analyst, Machine Learning Engineer, and BI Analyst. Some of the industries that employ are IT, banking, healthcare, and e-commerce. Salaries at entry level are 5-8 LPA, and experienced managers are likely to be 20+ LPA with great opportunities of growth.

Yes, our placement assistance is 100% including resume building, mock interviews and direct referrals to our hiring partners. Our group has networking with more than 100 companies in Noida and Delhi NCR. We are also going to offer you the unending support until you get the preferred job.

Our curriculum includes such fundamental tools as Python (NumPy, Pandas, Scikit-learn), SQL, Power BI, Tableau, and Advanced Excel. Your skills will include proficiency in statistical analysis, machine learning algorithms, and deep learning systems so that you will have the expertise to work in any Data Scientist position.

Absolutely. Noida is home to various IT giants such as HCL, TCS, Infosys, and Adobe and are aggressively recruiting Data Science professionals. The location incredibly close to the tech ecosystem of Delhi NCR offers a lot of prospects because there are estimated to be 97,000 vacant positions there. The average salaries also ensure that it is a good place to begin your career.

All the training sessions are recorded, you can watch the recording of the missed session. Also, we will provide you one on one doubt clearing session.

Yes, we have our Learning Management System where you will find Study Material, Assignments, Quizzes, Practice Sheets, Interview Preparation Material, Projects.

We give you the option to retake the course within one year of finishing it, which will help you more time to prepare for interviews.

Our batch size is usually from 5-10 students so that everyone can get individual attention.

Gyansetu team will assist you in software installation. You don’t need to pay anyone for the software installation.

Doubts sessions will be provided and our faculties will help you in resolving your queries during and after the course.

The duration of Data Science Training Course in Noida is usually from 6 to 9 months, depending on your pace of learning. There is no hurry from the institute, you can learn at your own pace.

We provide both online and classroom-based training with batches available on both weekdays and weekends.

Yes, Gyansetu’s Data Science Training Course in Noida includes industry based project scenarios, case studies, and assignments to ensure practical learning.

Students will learn SQL, Python, Power BI, Numpy, Pandas, MatplotLib, Jupyter, Scikit Learn, Keras as part of the Data Science Training in Noida.

Yes, after completing the Data Science Certification Course in Noida, you will receive an industry-recognized Nasscom approved Certificate.

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Frequently Asked Questions

Q1. What is Data Science and why is it significant?

Q2. Which Data Science institutions are the top in Noida?

Q3. What is the cost of a Data Science course at Noida?

Q4. How long is your Data science training?

Q5. Am I required to have experience in programming before I can commence this course?

Q6. Which are the career opportunities in the future of Data Science training?

Q7. Does it provide placement assistance upon course completions?

Q8. What will the tools and technologies that I will learn be?

Q9. Do Data Scientists have a chance to work in Noida?

Q10. What if I miss a class?

Q11. Do you provide learning content?

Q12. What if I am taking more time to learn or I want to repeat the course?

Q13. What is your average batch size?

Q14. How will I get the software installed?

Q15. What if I have a query after I complete the course?

Q16. What is the duration of Data Science Course in Noida?

Q17. Is Data Science Training in Noida available online or offline, with weekday or weekend classes?

Q18. Does this Data Science Course in Noida include practical projects?

Q19. What tools and technologies are taught in Gyansetu's Data Science Course in Noida?

Q20. Will I receive a certificate after completing Data Science Training Course in Noida?

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