NCC Intermediate Short Course in Data Science
This intermediate course provides a deeper understanding of data science — covering probability theory, statistics, data modelling, Python with SQL, data visualisation, and Natural Language Processing. Ideal for students who have completed an introductory data science course or have basic data knowledge.
Intermediate
Level
600 Hours
Total Duration
NCC Education
Awarding Body
Python + SQL
Key Tools
Course Overview
The NCC Intermediate Short Course in Data Science (Level 2 of 4 in the pathway) builds on introductory data science concepts with statistical techniques, data modelling, Python programming, SQL integration, data visualisation using Matplotlib, and an introduction to Natural Language Processing (NLP). Students who complete this course will be equipped for junior data analyst and business intelligence roles.
Entry Requirements
- Basic understanding of data science principles
- Prior completion of an introductory data science course (recommended)
- Competency in English
Course Modules
1
Introduction to Data Science
Data science workflow, tools, and professional applications
2
Probability Theory and Random Variables
Probability distributions, random variables, and statistical inference
3
Statistics Concepts
Descriptive and inferential statistics for data analysis
4
Linear Regression and Statistical Data Modelling
Regression analysis and predictive statistical modelling techniques
5
Introduction to Python
Python syntax, data structures, and programming for data science
6
Python with SQL
Integrating Python with relational databases using SQL
7
Visualisation with Matplotlib
Charts, graphs, and data storytelling with Python Matplotlib
8
Database Systems
Relational database architecture and management
9
Design and Develop Database System using SQL
Advanced SQL, schema design, and query optimisation
10
Text Mining and Natural Language Processing
NLP fundamentals, tokenisation, and text feature extraction
11
Text Classification
Sentiment analysis and document classification techniques
12
Text Clustering
Unsupervised learning methods for grouping text data
This is Level 2 of TNEDU's four-level Data Science short course pathway. Upon completion, students can progress to the NCC Advanced Short Course in Data Science for deep learning, advanced NLP, and production-level data pipelines.
Career Outcomes
Data Analyst
Junior Data Scientist
Database Manager
Business Intelligence Analyst
Progression Routes
NCC Advanced Short Course in Data Science → Deep learning, NLP, and production data pipelines
NCC Expert Short Course in Data Science → Big data, predictive analytics, and ML deployment
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