About the Course
What You'll Master
- Learn to extract meaningful insights from raw data — turning messy, unstructured information into decisions that drive businesses, governments, and research
- Master Python and its ecosystem for data analysis: NumPy for computation, Pandas for wrangling, Matplotlib and Seaborn for visualization
- Study statistics and probability not as abstract math but as practical tools for understanding uncertainty, running experiments, and making predictions
- Build machine learning models that learn from data — from linear regression and decision trees to deep neural networks and natural language processing
- Enter one of the highest-demand, highest-paying fields in tech, where every industry from healthcare to finance needs people who can turn data into strategy
Academic Staff (DTS)
- Dr. [DTS HOD]
- DTS Staff 1
Curriculum Courses
DTS201 (3U)DTS302 (3U)DTS304 (3U)DTS404 (3U)
The Survival Script
Your roadmap to becoming a data scientist. Each phase builds on the last — take your time and build genuine understanding.
Phase 01
Python & Mathematical Foundations
4–5 weeks
Python
NumPy
Jupyter Notebooks
Linear Algebra
Probability
Phase 02
Data Wrangling & Visualization
4–5 weeks
Pandas
Matplotlib
Seaborn
Data Cleaning
EDA
Phase 03
Statistics for Data Science
4–6 weeks
Hypothesis Testing
Bayesian Stats
A/B Testing
Distributions
SciPy
Phase 04
Machine Learning
6–8 weeks
scikit-learn
Regression
Classification
Clustering
Feature Engineering
Phase 05
Deep Learning & AI Applications
5–7 weeks
PyTorch
TensorFlow
CNNs
NLP
Transfer Learning
Phase 06
Portfolio & Career Launch
Ongoing
SQL
Kaggle Competitions
Portfolio Projects
Cloud Platforms
Communication