Engineering & Technology
Data Science & Artificial Intelligence
Data Science and Artificial Intelligence focuses on extracting useful insights from large volumes of data and using those insights to train intelligent machine systems. You will learn data mining, statistical modeling, machine learning algorithms, and big data visualization techniques.
Program objectives
- 01Learn to clean, analyze, and visualize large, complex datasets.
- 02Master predictive analytics and statistical modeling techniques.
- 03Build machine learning models to solve business and research problems.
- 04Understand big data engineering and modern cloud data storage.
Why choose this program
Data-driven decision era
Businesses rely on data analysts and AI models to make critical financial and market decisions.
Combines math, business, and tech
Ideal if you enjoy statistics, programming, and discovering practical business insights.
High-paying career paths
Data scientists and AI specialists are among the most sought-after tech professionals globally.
Skills you'll build
- Data wrangling and cleaning
- Statistical analysis and modeling
- Machine learning algorithms
- Data visualization (PowerBI / Tableau)
- Data storytelling
- Business acumen
- Critical thinking
Tools & software
- Python / R
- SQL
- PowerBI / Tableau
- Jupyter Notebooks
- Apache Spark / Hadoop
Challenges to expect
Academic
- Requires mastering rigorous statistical theory alongside programming and database systems.
Technical
- Handling messy, incomplete real-world datasets and cleaning them for accurate model training.
Financial
- Requires a high-spec laptop capable of processing heavy statistical operations and datasets.
Personal
- Requires patience when running repetitive data experiments to improve model accuracy.
Tips from the field
- Get very comfortable with SQL early—companies rely on SQL to pull raw database tables.
- Practice presenting your data findings clearly so non-technical managers can understand them.
- Build a portfolio on Kaggle showcasing real data analysis and visualization dashboards.
Career paths
- Data Scientist
- Data Analyst
- Machine Learning Engineer
- Business Intelligence (BI) Developer
- Big Data Engineer
Where you can study this
| Name | Latest cutoff | Tuition (annual) |
|---|---|---|
| Academic City UniversityBSc | — | — |
FAQs
What is the difference between Data Science and Artificial Intelligence?+
Data Science focuses on organizing, analyzing, and finding patterns in data. Artificial Intelligence uses those patterns to build software that makes automated decisions.
Do I need to be strong in statistics?+
Yes. Probability and statistics form the core mathematical foundation for making accurate data predictions.
What tools do Data Scientists use daily?+
They use Python, R, SQL databases, Jupyter Notebooks, and visualization dashboards like PowerBI or Tableau.
Can I work in banking with a Data Science degree?+
Yes. Banks hire data scientists for fraud detection, credit risk scoring, and customer behavior analysis.
What is data cleaning?+
Data cleaning is the process of removing errors, duplicate records, and missing values from raw datasets so models produce correct results.
How long does it take to learn Python for data science?+
Basic Python syntax takes a few weeks, while mastering data packages (like Pandas, NumPy, and Scikit-learn) takes continuous practice throughout your degree.
Related programs
Engineering & Technology
Aerospace Engineering
Aerospace Engineering trains you to design, build, and test aircraft and related flight systems -- covering aerodynamics, propulsion, and structural design. It's a demanding, highly technical field that positions graduates for work in aviation, aircraft maintenance, and emerging aerospace technology.
Engineering & Technology
Agricultural Engineering
Agricultural Engineering applies engineering principles to farming -- designing machinery, irrigation systems, and equipment that make agriculture more efficient. It's a bridge between engineering and agriculture, aimed at solving practical farming problems with technical solutions.
Engineering & Technology
Architectural Technology
Architectural Technology focuses on the technical side of how buildings are designed and put together -- construction methods, building materials, and technical drawings that turn an architect's vision into something that can actually be built. It's more hands-on and technical than a full Architecture degree.
Engineering & Technology
Architecture
Architecture trains you to design buildings -- balancing beauty, function, and safety while shaping the spaces people live, work, and gather in. It's a long, demanding program combining creative design with technical building knowledge, preparing you to eventually become a licensed architect.
Engineering & Technology
Artificial Intelligence
Artificial Intelligence (AI) teaches you how to build computer systems that can think, learn, and solve problems like humans. You will study machine learning algorithms, computer vision, natural language processing, and neural networks to create smart software and autonomous systems.
Engineering & Technology
Automobile Engineering
Automobile Engineering teaches you how vehicles -- cars, trucks, motorcycles -- are designed, built, and maintained. You'll study everything from engines and vehicle dynamics to automotive electronics, preparing you to work in the growing automotive and transport sector.