Best Data Science Course in Kochi

7 Months Duration

22 Modules Curriculum

Mon – Sat Schedule

Online & Offline Mode

4.8★ Google Rating

1000+ Placed Alumni

About This Course

Data Science is the most transformative career of the decade. At Techolas Kochi, our 7-month Data Science program equips you with everything from Python and statistics to machine learning, deep learning, and cloud deployment.

With 160+ hours of structured learning, 3+ real-world projects, and dedicated placement support, our graduates have secured roles at leading MNCs across IT, BFSI, healthcare, and consulting. Whether you're a fresher or looking to transition from another field, our mentors will guide you every step of the way.

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

Tools You'll Master

Python Pandas NumPy Matplotlib Seaborn Tableau Power BI TensorFlow Keras Scikit-learn AWS SQL

Course Curriculum

A 7-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

Python Syntax, Variables & Data Types
Lecture
Functions, Loops & OOP Basics
Hands-on
File Handling & Exception Management
Hands-on

Statistics & Probability for Machine Learning

Mathematical backbone of all ML models

Descriptive & Inferential Statistics
Theory
Probability Distributions
Lecture
Hypothesis Testing & p-values
Hands-on

Data Wrangling with Pandas & NumPy

Cleaning and preparing messy datasets

Pandas DataFrames & Series
Hands-on
Handling Missing Data & Duplicates
Hands-on
Data Merging, Grouping & Pivoting
Hands-on

Data Visualisation – Matplotlib, Seaborn & Tableau

Turning numbers into compelling stories

Matplotlib Charts & Customisation
Hands-on
Seaborn Statistical Plots
Hands-on
Tableau Dashboard Creation
Hands-on

Exploratory Data Analysis (EDA)

Deep-diving into real datasets

EDA Framework & Methodology
Theory
Real Dataset EDA – E-commerce
Project
Insights Reporting
Hands-on

Machine Learning – Supervised Algorithms

Regression and classification techniques

Linear & Logistic Regression
Hands-on
Decision Trees & Random Forest
Hands-on
SVM & K-Nearest Neighbours
Hands-on

Machine Learning – Unsupervised Algorithms

Clustering and dimensionality reduction

K-Means & Hierarchical Clustering
Hands-on
PCA for Dimensionality Reduction
Hands-on
Anomaly Detection
Hands-on

Model Evaluation & Hyperparameter Tuning

Building robust, production-ready models

Cross-Validation & Bias-Variance
Theory
Grid Search & Random Search
Hands-on
Model Selection Best Practices
Hands-on

Deep Learning Basics – Neural Networks

Introduction to AI-powered modelling

Artificial Neural Networks Explained
Theory
TensorFlow & Keras Setup
Hands-on
Building Your First Neural Network
Hands-on

Convolutional Neural Networks (CNN)

Image classification and computer vision

CNN Architecture & Layers
Theory
Image Classification Project
Project
Transfer Learning with VGG & ResNet
Hands-on

Natural Language Processing (NLP)

Extracting insights from text data

Text Preprocessing & Tokenisation
Hands-on
Sentiment Analysis Project
Project
Word2Vec & Transformer Basics
Theory

Power BI for Data Science Reporting

Publishing insights to business teams

Power BI Basics & DAX
Lecture
Building KPI Dashboards
Hands-on
Publishing & Sharing Reports
Hands-on

Big Data Basics – Spark & Hadoop Introduction

Handling data at scale

Big Data Ecosystem Overview
Theory
Apache Spark Basics with PySpark
Hands-on
MapReduce Concept
Theory

Cloud ML Services – AWS & Azure

Deploying models to the cloud

AWS SageMaker Introduction
Lecture
Azure ML Studio Walkthrough
Hands-on
Building a Cloud ML Pipeline
Hands-on

SQL for Data Scientists

Querying databases for analytics

Advanced SQL Joins & Subqueries
Hands-on
Window Functions & CTEs
Hands-on
SQL for ML Feature Engineering
Hands-on

Time Series Analysis & Forecasting

Predicting future trends from historical data

Time Series Concepts & Decomposition
Theory
ARIMA Forecasting
Hands-on
LSTM for Time Series
Hands-on

Recommendation Systems

How Netflix and Amazon power suggestions

Collaborative Filtering
Theory
Content-Based Filtering
Hands-on
Building a Movie Recommender
Project

Data Ethics, Privacy & AI Governance

Responsible data science practices

Bias in ML Models
Theory
GDPR & Data Privacy Basics
Lecture
Explainable AI (XAI) Concepts
Theory

Domain Applications – Finance, Healthcare, Retail

Applying DS across industries

Healthcare Predictive Analytics
Case-study
Financial Fraud Detection
Case-study
Retail Demand Forecasting
Case-study

Capstone Project – End-to-End Data Science Pipeline

Your portfolio centrepiece

Problem Definition & Data Collection
Project
Modelling & Evaluation
Project
Deployment & Presentation
Project

Career Prep – Resume, Portfolio & Placement Drive

Landing your first data science role

GitHub Portfolio & README Writing
Theory
Mock Technical & HR Interviews
Hands-on
Placement Drive & Job Referrals
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

₹500 Admission Fee Flexible installment options · Full fee disclosed at counselling

Duration 7 Months
Curriculum 22 Modules
Schedule Mon – Sat
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 →