Admission Fee Just ₹`1000 · ISO 9001:2015 Certified

Best Data Science Course in Kochi With Gen AI

Data Science is the art of turning raw data into meaningful insights and smarter decisions.

9 Months Mon – Fri Online & Offline 4.8★ 1000+ Placed

9 Months Duration

Mon – Fri Schedule

Online & Offline Mode

4.8★ Google Rating

1000+ Placed Alumni

About This Course

The Data Science with Generative AI program at Techolas Kochi is a 9-month, mentor-led course built for aspiring data scientists in Kochi, Ernakulam, and across Kerala. Starting with Python fundamentals, the curriculum progressively covers statistics, Pandas, NumPy, Matplotlib, machine learning, deep learning with TensorFlow and Keras, NLP, computer vision, cloud deployment, and MLOps — making it one of the most comprehensive Data Science training programs available in Kochi today.
Delivered in small batches from our Ernakulam campus, with both online and offline options, every module is taught by industry professionals with 8–12 years of experience. Freshers, commerce graduates, and career switchers from Kochi have all successfully transitioned into Data Scientist and ML Engineer roles through this program. With 3+ industry-grade projects and a dedicated placement team, 95% of Techolas Kochi's Data Science graduates secure placements within 4–6 weeks.

What You'll Learn

Master Python for data manipulation and analysis
Apply statistics and probability to real datasets
Clean and preprocess data with Pandas & NumPy
Create compelling visualisations with Matplotlib & Tableau
Build supervised and unsupervised ML models
Understand deep learning with TensorFlow & Keras
Apply NLP to text data and sentiment analysis
Deploy ML models to cloud platforms
Understand MLOps concepts for model deployment and monitoring
Gain hands-on experience through industry-level capstone projects

Tools You'll Master

Python Pandas NumPy Matplotlib Seaborn Power BI TensorFlow Keras Scikit-learn SQL R programming Microsoft Excel OpenCV NLTK

Course Curriculum

A 9-month mentor-led program to transform beginners into job-ready data scientists with 95% placement success and 1000+ alumni placed.

Introduction to Data Science & Career Scope

What data scientists do and how industries use DS

What is Data Science?
Theory
Career Pathways in Data Science
Lecture
Setting Up Python & Jupyter
Hands-on

Python Programming for Data Science

From basics to advanced Python scripting

Introduction to Python
Theory
Variables and Data Types
Lecture
Operators and Expressions
Lecture
Conditional Statements
Hands-on
Loops (for, while)
Hands-on
Functions and Modules
Hands-on
Object-Oriented Programming (OOP)
Lecture
File Handling
Lecture
Exception Handling
Lecture
Python mini projects
Project
Data manipulation scripts
Hands-on

SQL for Data Analysis

Introduction to DBMS

Introduction to Databases
Theory
CRUD Operations
Lecture
Joins (Inner, Left, Right)
Hands-on
Subqueries
Hands-on
Aggregate Functions
Hands-on
Views and Indexes
Lecture
Customer and Sales Analytics Database Project
Project
Windows functions
Hands-on
Filtering and sorting data
Hands-on
GROUP BY and HAVING clauses
Hands-on

Statistics for Data Science

Analysing datasets

Descriptive Statistics
Theory
Mean, Median, Mode
Theory
Variance & Standard Deviation
Theory
Probability Concepts
Theory
Probability Distributions
Theory
Correlation & Regression
Lecture
Hypothesis Testing
Hands-on
Statistical analysis using Python
Hands-on

Numpy for Data Science

Efficient Numerical Computing and Array Processing with Python

Arrays and vectorized operations
Hands-on
Mathematical and statistical functions
Lecture
Performance optimization
Lecture

Pandas for Analysis

Data Manipulation and Analysis with Python

Series and DataFrames
Lecture
Data cleaning and transformation
Hands-on
Handling missing values
Hands-on
GroupBy and aggregation
Hands-on
Data manipulation techniques
Lecture
Generating Python scripts using AI
Lecture
Debugging and optimizing code
Lecture
AI-generated EDA summaries
Lecture

Data Visualization (Matplotlib,Seaborn)

Visual Analytics with Python

Matplotlib Basics
Theory
Creating simple plots
Hands-on
Customizing plots
Hands-on
Introduction to Seaborn
Theory
Statistical Visualizations
Hands-on
Relationship Plots
Hands-on
Categorical Plots
Hands-on
Correlation Analysis
Hands-on

Machine Learning for Data Analysis

Predictive and clustering techniques used in analytics.

Introduction to machine learning
Theory
Machine learning workflow
Lecture
Supervised Learning
Hands-on
Model evaluation metrics
Hands-on
Unsupervised Learning
Hands-on
Intro to Reinforcement Learning
Lecture
AI-Assisted Model Interpretation
Lecture
Machine learning project
Project

Power BI

Data Analysis and Reporting

Data visualization
Theory
Introduction to Power Bi
Theory
Data Import and Connectivity
Hands-on
Data Transformation with Power Query
Hands-on
Data Modeling
Hands-on
Interactive charts & reports
Hands-on
DAX (Data Analysis Expressions)
Hands-on
Dashboard Design
Hands-on
Power BI with Copilot
Hands-on
Power BI Dashboard
Project

Microsoft Excel

Data Analysis and Spreadsheet Essentials

Excel interface and workbook structure
Lecture
Data types and formatting
Lecture
Logical, text, date, and lookup functions
Hands-on
Data cleaning techniques using formulas
Hands-on
Pivot tables and pivot charts
Hands-on
Interactive dashboards using slicers and visual elements
Hands-on
Excel with AI Integration
Lecture
Excel dashboard using Pivot tables and charts
Project

R Programming

Statistical Computing and Data Analysis

Introduction to R
Theory
Variables and Data Types
Lecture
Operators and Expressions
Hands-on
Conditional Statements
Hands-on
Loops (for, while)
Hands-on

Deep Learning

Neural Networks and AI Applications

Neural Network Fundamentals
Theory
TensorFlow & Keras
Lecture
Introduction to Deep Learning
Theory
Artificial Neural Networks (ANN)
Hands-on
Convolutional Neural Networks (CNN)
Hands-on
Transfer Learning
Hands-on
Recurrent Neural Networks (RNN)
Hands-on
Long Short-Term Memory (LSTM)
Hands-on
Gated Recurrent Unit (GRU)
Lecture
End-to-End Data Science Project
Project

Natural Language Processing (NLP)

Processing and Analyzing Text Data

Introduction to NLP
Theory
Text Preprocessing
Hands-on
Word Embeddings
Hands-on
Sentiment Analysis
Hands-on

Computer Vision

Image Processing and Visual Intelligence

Introduction to Computer Vision
Theory
OpenCV Basics
Lecture
Feature Detection
Hands-on
Object Detection
Hands-on
Face Detection and Recognition
Hands-on
Video Processing
Hands-on
CNN-Based Image Analysis
Hands-on

Recommendation Systems

Intelligent Recommendation Techniques

Content-Based Filtering
Hands-on
Collaborative Filtering
Hands-on
Hybrid Systems
Hands-on

Generative AI

Generative Models for Modern AI

Introduction to GenAI
Theory
Large Language Models (LLMs)
Lecture
Prompt Engineering
Hands-on
Text, Image & Code Generation
Hands-on
GenAI Use Cases
Lecture

Git & GitHub

Git & GitHub for Data Analytics

Version Control Concepts
Lecture
Git vs GitHub
Lecture
Git Installation & Configuration
Hands-on
Core Commands (init, add, commit, log)
Hands-on
Branching & Merging
Hands-on
Pull Requests
Hands-on
Repository Management
Hands-on
Professional README Creation
Hands-on
GitHub Portfolio Building
Hands-on

Cloud Computing for Data Science

Cloud Fundamentals
Theory
AWS / Azure / GCP Overview
Lecture
Cloud Storage & Compute
Lecture
Deploying ML Models
Hands-on
Cost & Scalability
Lecture

MLOps

ML Deployment and Monitoring

ML Lifecycle
Lecture
Experiment Tracking
Hands-on
Model Versioning
Hands-on
CI/CD for ML
Hands-on
Monitoring & Retraining
Hands-on

Agentic AI & AI Agents

AI Agents for Intelligent Workflows

Introduction to Agentic AI
Theory
Autonomous Decision Systems
Theory
AI Agents & Tool Usage
Hands-on
Single-Agent vs Multi-Agent Systems
Lecture

Capstone Project

End-to-End Data Science Project
Hands-on
ML/DL Implementation
Hands-on
GenAI Integration
Hands-on
Cloud Deployment
Hands-on
MLOps Pipeline
Hands-on
GitHub Documentation
Hands-on

Student Reviews

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Frequently Asked Questions

Anyone with basic computer knowledge can join. Fresh graduates, working professionals, career switchers, and non-IT candidates are all welcome. No prior coding or maths background is required.

No. Python programming and the required mathematics are taught from scratch within the course. Most of our successful students had no prior coding experience.

Yes. The curriculum covers supervised and unsupervised ML, deep learning with TensorFlow/Keras, NLP, and cloud ML services on AWS and Azure.

Highly practical. You will work on 3+ real-world projects across healthcare, finance, and retail, plus a full capstone project you'll deploy to the cloud.

Yes. Our dedicated placement team provides resume building, LinkedIn optimisation, mock interviews, and direct referrals to hiring companies. 95% of our graduates are placed.

You will receive three certificates: a NACTET certificate, an ISO-certified Techolas Course Completion certificate, and an Internship certificate.

Absolutely. Commerce graduates, MBA holders, science graduates, and career switchers are among our most successful alumni.

Entry-level data scientists typically earn ₹6–8 LPA. With 2–3 years of experience, professionals in this field earn ₹12–20+ LPA.

🔥 Next Batch: 19 Jan 2026 6 Seats Left

₹1,000 Admission Fee Flexible installment options · Full fee disclosed at counselling

Duration 9 Months
Schedule Mon – Fri
Mode Online & Offline
Google Rating 4.8★
Alumni 1000+ Placed

Secure Your Seat Call: +91 7356713111

Top Hiring Companies

Infosys

TCS

Wipro

Cognizant

Accenture

Certificates You'll Earn

NACTET Certificate

NACTET — Nationally recognised industry credential

Course Completion Certificate

Techolas — ISO 9001:2015 certified achievement

Internship Certificate

Techolas — Pre-placement practical experience validation

Why Choose Techolas?

Limited Batch Size

15–30 students per batch for individual mentorship & focus

95% Placement Success

Documented alumni outcomes with dedicated placement support

Real-World Projects

3+ industry-grade projects & case studies in the curriculum

Mentor-Led Training

Senior professionals with 8–12 years of industry experience

Transparent Outcomes

Public alumni success stories and verified placement data

Affordable & Flexible

Start with ₹500 admission fee; installment options available

Hybrid Mode

Attend online or offline with live mentor support & recordings

ISO 9001:2015 Certified

Institute certified to global quality standards

Success Stories

Real students. Real placements. View more on Instagram →

95% Placement Rate

1000+ Alumni Placed

4–6 Wks Avg. Placement Time

4.9★ Google Rating

After This Course

Career Outcomes & Salaries

Data Scientist

₹6 – 12 LPAAvg. Annual Package

Machine Learning Engineer

₹6 – 14 LPAAvg. Annual Package

Data Analyst (Advanced)

₹4 – 8 LPAAvg. Annual Package

AI/ML Research Associate

₹7 – 12 LPAAvg. Annual Package

Deep Learning Specialist

₹7 – 14 LPAAvg. Annual Package

NLP Engineer

₹7 – 13 LPAAvg. Annual Package

AI Consultant

₹10 – 18 LPAAvg. Annual Package

Big Data Engineer