Data Science Course in Kerala

Gain practical experience and get expert instruction from the pros. This is the practical knowledge that best jobs in Kerala companies look for. Enroll now and begin your journey to a lucrative career in data science!

4.8 (8921 Reviews)

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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: 27 Dec, 2025

Next Batch: 27 Dec, 2025

Overview
Features
Placements
Certification
Curriculum
Projects
Reviews
FAQs

Data Science Course in Kerala Overview

The Data Science course in Kerala will help you understand the fundamentals of Python programming and how it is used to analyze data, perform predictive analytics, and build machine learning models.

You will learn theory along with them, and also pursue hands-on practice, that you got to see us performing in our premises, so that you will gain healthcare job related real time experience.

Some of the important ones are: extensive modules on Python, data visualization, machine learning.

Real-world tasks that apply your learning in the classroom to things you can do.

Learning the most current tools and techniques that the top employers are seeking today.

At the core of what will power the analytics industry in the years to come is Data science, machine learning and python. The U.S. Bureau of Labor Statistics predicts that jobs will increase by 35 percent from 2022 to 2032. Kerala with its booming IT hubs like Technopark and Infopark is soon turning out to be a hub for analytics and AI careers. I guess this is good news for people who are skilled at translating data into actionable business insights.

Data Science Training in Kerala

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 in Kerala

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 Kerala

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 Kerala

Upon completion of this course, you will get a Certificate from the industry which is widely recognized. With this, you’ll be able to expand your job potential into analytics, business intelligence and AI-driven decision-making.

More Money to Make:- Certified professionals earn 20% more than their non-certified counterparts, a study from IBM Skills Network and LinkedIn Learning found.
Accelerated Career Growth:- The leading IT, fintech and analytics companies in Kerala have shown strong inclination to retain certified professionals for promotions and management roles.
Instant Credibility:- With this certification you have shown that you’re hardworking and know a thing or two about technology; staying ahead in the fast paced landscape of analytics.

Paste your certificate in LinkedIn Profile, Meta and Other Professional website’s so that Kerala’s Top IT companies and recruiters can notice you.

Enquire Now

Data Science Course Curriculum

The Gyansetu Data Science Master Certification training in Kerala gives you practical, real workspace oriented education that prepares you for dealing with data handling problems of real time analytics.

SQL

You will learn what it takes to manage databases at the enterprise level in the SQL Developer Certification training in Kerala. For you to become a skilled designer and developer of data under Big Data, make sure you study the following: SQL Operators SQL Functions Subqueries Stored Procedures User-defined Functions Database Concurrency SQL Optimization & Performance Tuning

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

Through Gyansetu’s Power BI Certification in Kerala, you will gain the knowledge to create interactive dashboards and business reports using real-life projects. If you want to be a Certified Power BI Professional, study DAX formulas and advanced data modeling and how to design charts and graphs. That is a skill that many of the best employers in Kerala are looking for.

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 Certification Course in Kerala covers all the core topics as well as Web Scraping, Numpy, Pandas, Data Exploration and Automation and API Integrations. By the end, you’ll have the skills to solve real business problems on the job using Python.

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

Probability, descriptive statistics, hypothesis testing, normal distribution and sampling are all included in the Statistics for Data Science Certification in Kerala. All of these are necessary skills that one should possess before making a start into learning machine learning.

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

The Best Machine Learning Training in Kerala covers everything there is to know about supervised and unsupervised learning, dimensionality reduction, deep learning, artificial intelligence and reinforcement learning. This will get you ready for high-stress AI and ML jobs.

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 Kerala

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 Kerala

Why should you get your Data Science Certification in Kerala from Gyansetu?

Gyansetu’s Data Science Certification in Kerala is the best choice because it has a curriculum designed by experts that is in line with what employers want, so you learn the most useful skills. You will learn about Python, SQL, Machine Learning, Power BI, and Generative AI through hands-on work on real-world projects.

How long does the data science course last?

The course duration completely depends on you and the batch you wish to choose. At Gyansetu, you have the option to choose classes on weekdays and weekends. This makes it easy for working people and students to fit their learning around other things they have to do.

I'm currently working in IT. Will you help me find a job?

Yes, Gyansetu will help you to switch jobs. This will help you to make a resume and conduct mock interviews. Our placement team helps students get a job based on their experience and skills.

Of course! The course is for people who are new to IT or don’t work in IT. We start our course with the basics to advance.

Yes, Gyansetu helps new graduates, students, and people who have been out of work for a while by giving them personalized placement support. You’ll get help with your resume, practice interviews, and access to job openings to help you get a job in data science, even if you have a gap in your profile.

Yes, Gyansetu has a free demo session where you can talk to trainers, learn about the teaching style, and look over the course structure before you sign up. This helps you make a smart choice before you sign up.

Don’t worry if you miss a live class; all sessions are recorded and sent to students who are enrolled. You can watch the recordings whenever you want, or you can go to the same session with a different group to catch up.

Yes, we provide learning materials which include recorded lectures and projects. You can use these resources to have a better grasp of data science topics.

You can take the course again for free if you need more time to understand the material. This flexibility makes sure you understand the material completely before moving on in your career.

Gyansetu keeps its batch size small. So that the teachers can pay attention to every student to solve their queries and make their learning experience better.

Yes, we offer weekend batches for people who are working. This flexibility helps students to learn more about data science while working.

Our trainers will help you to install software like Python, SQL, and Power BI by providing a step-by-step guide. If you need it, you can also get help with remote installation to make sure the software is set up correctly.

You can still ask questions and get answers from your trainers even after the course is over. You’ll also have access to recorded lectures for the rest of your life, so you can go back and review ideas whenever you need to.

Gyansetu is one of the best data science courses in Kerala because it helps students find jobs, has hands-on projects, and teaches things that are useful in the real world. The structured training and career help make sure you are ready for a job with confidence.

Gyansetu is the best choice for beginners because it starts with the basics, doesn’t require any coding knowledge, and gives step-by-step training. The placement help also helps people who are new to the field get their first job in data science.

Gyansetu is the best online data science course in Kerala because it has both live and recorded classes. The interactive training makes sure that you can get your questions answered right away while you learn from home.

The cost of the course ranges from ₹30,000 to ₹2,00,000, depending on how long and how deep it is. Gyansetu also has easy EMI plans to help you pay for things. To know more, you can contact our support team on +919999201478.

Anyone with a master’s degree, whether they are technical or not, can sign up. The course is meant to teach students how to code from the ground up, so they don’t need any prior experience.

Yes, data science is a high-paying job that is in demand in most industries. Companies are looking for data scientists to work on analytics, AI and machine learning.

Freshers in the field of data science can easily make upto Rs. 6-8 LPA, while experienced workers make upto Rs. 10-18 LPA. The salary package depends on your skills and company’s standards.

There is no strict grade requirement; all you need is knowledge of math and statistics, which will help you to understand things better.