Data Science Course

Data Science with Python and R

Embark on a transformative Data Science journey in Kolkata. Master key concepts, tools, and techniques through practical training. Elevate your career with our cutting-edge curriculum. Enroll now to unleash the potential of data science in the vibrant city of Kolkata.

New Batch Starting:

15th Nov, 2026

For Prebooking Call - 9903376367

And get a free AI toolkit

Data Science Course in Kolkata

Looking to accelerate your career in Data Science Course in Kolkata? Look no further than Data Brio Academy’s Data Science certification program. Our program is designed and taught by experts who are defining world standards in the field.

In our data science course in Kolkata, you will gain hands-on experience in data exploration, data visualization using various tools like Tableau, Microsoft PowerBI, SQL, and MS Excel. You will master statistical analysis, predictive analytics, NLP, and Machine Learning models (supervised and unsupervised) with a focus on model evaluation using R and Python languages.

Our course is designed to provide a comprehensive understanding of the complete data science project lifecycle through industry cases, capstone projects, and 1:1 project mentoring. You will gain practical, hands-on experience in each step of the project lifecycle, from data collection and cleaning to model building and evaluation.

With our Data Science Course, you will gain the skills and knowledge necessary to excel in your data science career in Kolkata. Our program is designed to prepare you for success in the rapidly growing field of data science and AI.

Join our Data Science Course Training in Kolkata today and take the first step towards a successful career in this exciting and dynamic field!

Why Data Brio Academy?

Get individual attention from faculties who are successful industry practitioners/leaders in data science and passionate about your learning
Go beyond using only functions and standard libraries of R/Python/SAS. Understand fundamentals of ML/AI for working in projects. Work hands-on real-life cases and industry projects with mentoring/guidance and create your project portfolio.

Get mentored by Expert AI Panel member for European Observatory of ICT AI Standards by EU; Editor of 1st international assessment standard on Big Data Analytics, Chair of ISO AI sub-committee; Patent owners in AI
Attend classes online from your home or face-to-face at the academy as per your convenience
Access video recording of live classes if you missed a session or for revisiting a topic whether you attend online or in classroom at the academy

Who this course is for:

Students and early-career professionals
Freshers and working Professionals in IT, DW, MIS, reporting, etc. who work with data
Business professionals in marketing, Finance, HR, Supply chain, etc. from the industry verticals of Manufacturing, Telecom, IT, Banking & Financial Services, FMCG, Hospitality, Healthcare, etc. who want to use data for decision-making
Professionals who want to start or shift to a career in data analytics

Eligibility

Training and Placement

Subsequent to the completion of our Data Science Certification course, assignments, projects, and placement assistance will kick start with resume building. Mock Interviews will be conducted for a better understanding of their interview readiness, one-to-one discussion on job description during interview calls, etc. This helps the participant to retrospect and understand their capability to improve the readiness. Participants can attend and successfully crack the interviews with complete confidence.

Students Successfully Placed in Companies:

Is the Data Brio Academy Data Science with Gen AI course fee affordable?

Course fee:

₹ 52,000

+ GST applicable

With Money Back Guarantee**

What's included:

Registration fee:

₹ 7,000

+ GST applicable

Discount* and EMI option available.

What real-world projects will I work on during the course?

Build a professional portfolio in Data Science, AI, and Data Engineering through real-world projects with industry experts, guided by mentorship and internship.
Showcase your work through an industry-ready portfolio that strengthens your profile for top career opportunities.

Projects and Application

Analytics Dashboard using Power BI and SQL

Beginner to Intermediate

Learn how to perform HR analytics using SQL and Power BI with a real‑world case study. Cover data cleaning, exploratory analysis, HR KPIs, and interactive dashboard building for data‑driven workforce decisions.

Power BI

EDA

HR Dashboard

SQL

Data Cleaning

Data Visualization

Feature Selection

HR KPIs

Predicting User Behaviour through AI Based Clickstream Analysis

Advanced

Learn how to analyze customer clickstream data using AI and machine learning to understand and predict user behavior. This project focuses on data wrangling and sequence analysis using advanced techniques such as LSTM‑based deep learning, enabling learners to model user journeys and uncover meaningful marketing insights.

Clickstream Analysis

Data wrangling

LSTM

Machine Learning

Marketing Analytics

Customer Behaviour

Deep Learning

Manufacturing Disc Brakes – defect reduction using machine learning

Intermediate

Learn how to apply machine learning in a manufacturing context through a real world disc brake production case study. This project focuses on analyzing manufacturing and quality data to identify defect patterns and predict failure risks.

Manufacturing

Feature engineering

Defect patterns

Predictive model

Logistic Regression

SVM

Anomaly detection

Industry Capstone Projects

Every student is required to complete a comprehensive capstone project that involves working with real-world data and solving actual business challenges in collaboration with our industry partners. These projects not only demonstrate practical expertise but also significantly enhance a candidate’s resume and provide strong, credible discussion points during job interviews.

Forecasting Project – Product & SKU Level Demand Prediction

Beginner to Intermediate

A hands on forecasting project where learners apply time series and machine learning methods to predict future sales, covering the complete lifecycle from data cleaning and model training to evaluation and forecast generation for data driven business planning.

Demand forecasting

Machine learning

ARIMA

Time series analysis

Prophet

Python

Evaluation metrics

AI Chatbot for Insurance – Customer Support using LLMs and RAG

Advanced

Build an intelligent insurance chatbot using LLMs, RAG, computer vision models for document understanding and agentic AI to automate customer support and policy related queries.

Insurance

Chatbot

RAG

LLM

Computer vision

Customer support

Generative AI

Azure AI

Python

Agentic AI

Product Recommendation using AI

Advanced

Apply machine learning and GenAI to design intelligent, personalized product recommendations and optimize marketing campaign performance.

AWS

Python

Databricks

Gen AI

Market basket

Customer proximity models

Accredition & Affiliation

Data Science Course Curriculum

Duration – 120 Hours

Data Science Methods and Models

Analytics Fundamentals

Population and Sample
Elementary Probability, Correlation
Point & Interval Estimation
Hypothesis Testing, Type I & Type II Error, P-Value
Basics of Inferential analytics

Inferential Statistics

Normality Test
1- Sample and 2-Sample Tests
HOV, ANOVA, Moods Median Test, Chi-square test etc
Assignments with data sets

Modelling

Linear Regression
Assumptions and Diagnostics
Interactions and indicator variables
Descriptive & predictive models
Logistic Regression

Machine Learning Techniques

Clustering technique
Decision Tree
Case studies

Dimension Reduction

Multivariate Analysis
Factor Analysis
Case studies

Business Forecasting

Time Series data
Methods – MA, Exponential Smoothening, ARIMA
Evaluating best forecasts

Deep Learning & AI

Generative AI (GenAI) – Large Language Models (LLM) and RAG
Image Cognition (Video, Image)

R Programming for Data Science

Introduction to the R language and the computing environment

The R console, and the command interpreter
R scripts and running R scripts
The RStudio GUI and R Packages
Getting help in R and R functions

Data Structures

Basic object – Vector & operations
Data structures – matrices, lists, arrays, data frames
Manipulating data structures
Reading and writing data from and to different file formats

Data Management

The apply family of functions and its uses in efficient data processing
Basic string and date processing
Generating and using (pseudo) random samples

Writing R Functions

Basic R built-in functions
Recycling, Control flow, Recursion
Conditions, loops
Vectorization & vector Operation
Writing and using user-defined functions

Visualization in R

Simple charts and graphs – histograms, scatter diagrams
Line plots, boxplots, pareto charts, etc.
Plot function

Data Science applications using built-in R functions

Descriptive statistics
Hypothesis tests and ANOVA
Linear Regression including interactions and indicator variables
Machine learning algorithms

Python Programming

Python Fundamentals

Getting, installing & navigating the software
Anaconda IDE, Jupyter, Spider, Pycharm, Google colab
Statements and comments
Input, Output and Import
Python operators, variables

Data Types

Python numbers, string
Python list, Tuple, String, Set, Dictionary etc.
Dataframes, Modules, Packages
Conversion between data types

Data Structure

Troubleshooting and error handling
Conditionals
Functions – new and built-in function
Flow Control – If – Else, For loop, while loop etc.
Break & control

Data Management & Visualization

Data Management, Visualization and Basic analytics using libraries – Pandas, Numpy, Scipy, Scikitlearn, Matplotlib, Seaborn, Plotly etc.

Data Science & ML algorithms in Python

Descriptive statistics
Linear Regression including interactions and indicator variables
Machine learning algo in python – Classification & Regression, Decision Tree
Time-series forecasting

Analytics & Visualisation

Data and AI Paradigm

What is analytics, data science, ML, AI?
Data – Different perspectives and types
Sources of Data – public data, business data
Structured and unstructured data

Summaries and Visualizations

Central tendency, dispersion, cross tabulations
Association, covariance, correlation
Trend, seasonality, line chart
Histogram, boxplot, scatter plot, pareto chart etc.
Derived metrics & KPI

MS Excel for Analytics

Using formula & data validation
Pivot table and charts, Conditional formatting
Lookups, error handling
Numerical and graphical summaries

PoweBI or Tableau for dashboard

PowerBI or Tableau workspace – dimensions & measures
Tables & charts, various data source connectivity
Filters – slicing & dicing of multi-dimensional data
GIS-based visualization, time-series data
Calculated fields, Interactive dashboards

SQL for Querying and Databases

Basics of RDBMS
Tables & queries (select queries – group by, order by, having etc.)
Keys & joins (left, right, inner, outer)

S/W tools

Python & Google colab
MS Excel or equivalent
Tableau / PowerBI
MySQL or equivalent

Our Certificates

Gain Industry-Recognized Certificates in Data Science with Python and R

The course has the right balance…

The course has the right balance between theory and practical which is valuable for understanding. This course provided me exposure to real-time projects and also gave me the first job in my data science career.

Souvik Saha, (B.Com)

Data Analyst, UST Global

Anybody looking for a career…

Anybody looking for a career in data science, I would suggest them to go to Data Brio Academy not only for their expertise in the subject but because of the industry exposure the team has and the eco-system they provide for learning data science and AI.

Prosun Sikdar, (MBA)

Senior Advisor - Dell Technologies

DBA provided ample exposure…

DBA provided ample exposure to practical projects in data science with emphasis on understanding the project life cycle. This course helped me shift into data science role in one of the ‘big’ consulting firms from telecom networking.

Sumit Singh, (B.Tech)

Senior Analyst, EY

Very knowledgeable instructors…

Very knowledgeable instructors with real-world experience, which is very important for anyone interested in moving into the data science field.

Rajiv Menon

Project Manager, IBM

Overall experience is great…

Overall experience is great. Interaction with faculties helped me gain knowledge and motivated me towards pursuing a career in analytics and data science.

Soumil Mukherjee, (B.Tech)

Data Analyst - Koch Industries, USA

I am a scientist. My every day research…

I am a scientist. My every day research work involves lot of data analysis including quite involved statistical techniques and even in that context the data science course at DBA has been very useful for me. The faculty who took the bulk of the course is a brilliant teacher.