Program Overview

Data Science is a rapidly growing field that combines statistics, computer science, and domain knowledge to extract meaningful insights from data. This course introduces learners to the fundamental tools and techniques used in data science, including data preprocessing, exploratory data analysis, machine learning, and data visualization. The programme prepares participants for real-world, data-driven decision-making using Python and industry-standard libraries, making it ideal for beginners and career transitioners.

Certificate

Included

Who this is for

Individuals with little or no prior experience in data science
Learners interested in solving real-world problems using data and Python
Undergraduate or postgraduate students (CS, Engineering, Business, Statistics)
Fresh graduates seeking data science skills
Working professionals transitioning into data-related roles
Analysts or developers aspiring toward ML/AI careers

How to apply

pdu@iit.ac.lk

Apply View Fees

Next / Start

2026-04-13

Time

Tue & Thu, 6:30 PM – 8:30 PM

Introduction to Data Science

What is Data Science?
Real-world applications and domains
Data science workflow and lifecycle
Roles: Data Analyst vs Data Scientist vs ML Engineer
Tools and environments overview (Python, Jupyter Notebook, etc.)

Data Cleaning & Preprocessing

Handling missing data
Removing duplicates and correcting data types
Outlier detection and treatment
Encoding categorical variables
Feature scaling and normalization
Data transformation techniques

Exploratory Data Analysis (EDA) & Visualization

Descriptive statistics
Univariate, bivariate, and multivariate analysis
Data visualization using Matplotlib and Seaborn
Correlation heatmaps and pattern detection
Drawing insights to inform modeling

Feature Engineering

Feature selection techniques
Feature extraction (text and vector features)
Creating new variables from existing data
Handling skewed data (log transformations, binning)

Supervised Learning

Overview of predictive modeling
Regression: Linear Regression
Classification: KNN, Decision Trees
Model evaluation metrics (accuracy, precision, recall, F1-score)
Cross-validation and hyperparameter tuning

Unsupervised Learning

Clustering: K-Means, Hierarchical Clustering
Dimensionality reduction (PCA overview)
Customer segmentation and anomaly detection
Evaluating clustering results

Natural Language Processing (NLP)

Text preprocessing (tokenization, stemming, stopword removal)
Bag-of-Words and TF-IDF
Named Entity Recognition (NER)
Sentiment analysis basics
Word2Vec and RNN concepts

Introduction to Deep Learning

Neural network architecture (perceptron, layers, activation functions)
Forward and backward propagation (conceptual)
TensorFlow and Keras overview
Applications in image classification and NLP

Certificate

Included

Who this is for

Individuals with little or no prior experience in data science
Learners interested in solving real-world problems using data and Python
Undergraduate or postgraduate students (CS, Engineering, Business, Statistics)
Fresh graduates seeking data science skills
Working professionals transitioning into data-related roles
Analysts or developers aspiring toward ML/AI careers

How to apply

pdu@iit.ac.lk

Apply View Fees

Next / Start

2026-04-13

Time

Tue & Thu, 6:30 PM – 8:30 PM

Program Overview

Certificate

Included

Who this is for

Individuals with little or no prior experience in data science
Learners interested in solving real-world problems using data and Python
Undergraduate or postgraduate students (CS, Engineering, Business, Statistics)
Fresh graduates seeking data science skills
Working professionals transitioning into data-related roles
Analysts or developers aspiring toward ML/AI careers

How to apply

pdu@iit.ac.lk

+94 77 056 6577

Apply View Fees

Next Start

2026-04-13

Time

Tue & Thu, 6:30 PM – 8:30 PM

Introduction to Data Science

What is Data Science?
Real-world applications and domains
Data science workflow and lifecycle
Roles: Data Analyst vs Data Scientist vs ML Engineer
Tools and environments overview (Python, Jupyter Notebook, etc.)

Data Cleaning & Preprocessing

Handling missing data
Removing duplicates and correcting data types
Outlier detection and treatment
Encoding categorical variables
Feature scaling and normalization
Data transformation techniques

Exploratory Data Analysis (EDA) & Visualization

Descriptive statistics
Univariate, bivariate, and multivariate analysis
Data visualization using Matplotlib and Seaborn
Correlation heatmaps and pattern detection
Drawing insights to inform modeling

Feature Engineering

Feature selection techniques
Feature extraction (text and vector features)
Creating new variables from existing data
Handling skewed data (log transformations, binning)

Supervised Learning

Overview of predictive modeling
Regression: Linear Regression
Classification: KNN, Decision Trees
Model evaluation metrics (accuracy, precision, recall, F1-score)
Cross-validation and hyperparameter tuning

Unsupervised Learning

Clustering: K-Means, Hierarchical Clustering
Dimensionality reduction (PCA overview)
Customer segmentation and anomaly detection
Evaluating clustering results

Natural Language Processing (NLP)

Text preprocessing (tokenization, stemming, stopword removal)
Bag-of-Words and TF-IDF
Named Entity Recognition (NER)
Sentiment analysis basics
Word2Vec and RNN concepts

Introduction to Deep Learning

Neural network architecture (perceptron, layers, activation functions)
Forward and backward propagation (conceptual)
TensorFlow and Keras overview
Applications in image classification and NLP

Certificate

Included

Who this is for

Individuals with little or no prior experience in data science
Learners interested in solving real-world problems using data and Python
Undergraduate or postgraduate students (CS, Engineering, Business, Statistics)
Fresh graduates seeking data science skills
Working professionals transitioning into data-related roles
Analysts or developers aspiring toward ML/AI careers

How to apply

pdu@iit.ac.lk

+94 77 056 6577

Apply View Fees

Next Start

2026-04-13

Time

Tue & Thu, 6:30 PM – 8:30 PM

Fundamentals of Data Science: Build Your Future With a Data Science Course at IIT

Turn Data Into Meaningful Insight

In a world shaped by information, the ability to understand and use data is no longer a specialised skill - it's a powerful advantage. The Fundamentals of Data Science programme at IIT is designed for those who are curious about how data works and how it can be used to solve real problems. This data science course introduces you to the core concepts, tools, and thinking patterns that define one of today's most exciting and in-demand fields.

A Strong Foundation for a Data Driven World

This programme is carefully structured to give you a solid grounding in data analysis, statistical methods, and machine learning techniques. But it doesn't stop at theory. You will also develop practical skills in programming and data visualisation, helping you understand not just how to analyse data, but how to communicate your findings effectively. Through guided learning and hands-on experience, you begin to see how raw data can be transformed into meaningful insights. Whether it is identifying patterns, making predictions, or supporting decisions, the Fundamentals of Data Science course prepares you to think critically and work confidently with data.

Why Learn Data Science?

Data science is becoming essential across industries - from technology and healthcare to finance, retail, and government. Organisations rely on data to guide decisions, improve performance, and innovate. By following a data science course early in your academics or professional journey, you position yourself with skills that are not only relevant today, but increasingly valuable in the future.

A Pathway To Endless Opportunities

One of the most exciting aspects of data science is its versatility. It brings together ideas from computer science, mathematics, statistics, and business. This interdisciplinary nature means that the skills you develop can open doors to a wide range of career paths and further studies. At IIT, the focus is on helping you build both knowledge and confidence. By the end of the programme, you will have a clear understanding of how data can be used to create impact - and the ability to apply that knowledge in meaningful ways.

Professional Certificate in Fundamentals of Data Science • Level 01 – Foundation Certificates

Who this is for

Introduction to Data Science

Data Cleaning & Preprocessing

Exploratory Data Analysis (EDA) & Visualization

Feature Engineering

Supervised Learning

Unsupervised Learning

Natural Language Processing (NLP)

Introduction to Deep Learning

—

Who this is for

Who this is for

Introduction to Data Science

Data Cleaning & Preprocessing

Exploratory Data Analysis (EDA) & Visualization

Feature Engineering

Supervised Learning

Unsupervised Learning

Natural Language Processing (NLP)

Introduction to Deep Learning

—

Who this is for

Fundamentals of Data Science: Build Your Future With a Data Science Course at IIT

Turn Data Into Meaningful Insight

A Strong Foundation for a Data Driven World

Why Learn Data Science?

A Pathway To Endless Opportunities

Fundamentals of Data Science: Build Your Future With a Data Science Course at IIT

Turn Data Into Meaningful Insight

A Strong Foundation for a Data Driven World

Why Learn Data Science?

A Pathway To Endless Opportunities

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