Data Science is “The ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it — and that’s going to be a hugely important skill in the next decades.”
The Computer Science department at USAL offers a Bachelor of Science (B.S.) with a concentration in computing for Data Science. The program provides students with cross-disciplinary knowledge and skills in computer science, mathematics, statistics, and information visualization, to pursue effective careers in computing and data science.
The main focus of this program is turning data into useful knowledge through artificial intelligence and machine learning. Graduates will gain the skills in collecting and analyzing data, solving problems using intelligent techniques, and effectively communicating the solutions. Such skills are required in almost all industries making skilled data scientists increasingly demanded in companies all over the world. This field opens the door to diverse professions such as data analyst, data consultant, machine learning scientist, and data architect.
Courses distribution plan – Computing for Data Science Undergraduate Program
First year – fall
| Code | Course Name | Nb of weeks | Nb of Lecture hours | Nb of labs hours | credits |
| MATH203 | Linear Algebra | 15 | 30 | – | 3 |
| ENG 201 | English Communication skills I | 15 | 45 | – | 3 |
| ARAB201 | Arabic Communication skills | 15 | 45 | – | 3 |
| CSCI201 | Introduction to programming | 15 | 45 | 30 | 4 (3; 1) |
| CSCI 205 | Computer Science Overview | 10 | 15 | – | 1 |
| Total | 14 | ||||
First year – spring
| Code | Course Name | Nb of weeks | Nb of Lecture hours | Nb of labs hours1 | credits |
| MATH210 | Discrete Mathematics | 15 | 45 | – | 3 |
| ENG202 | English Communication Skills II | 15 | 45 | – | 3 |
| CSCI203 | Object Oriented Programming | 15 | 45 | 30 | 4 (3; 1) |
| CSCI210 | Computer Architecture and Organization | 15 | 30 | – | 3 |
| MATH 201 | Calculus | 15 | 30 | – | 3 |
| Total | 16 | ||||
First year – summer
| Code | Course Name | Nb of weeks | Nb of Lecture hours | Nb of labs hours | credits |
| CSCI212 | Computer Networks – I : Networking fundamentals | 8 | 45 | – | 3 |
| GE/DE | Elective I | 8 | 45 | – | 3 |
| Total | 6 | ||||
Second year – fall
| Code | Course Name | Nb of weeks | Nb of Lecture hours | Nb of labs hours | credits |
| CSCI311 | Introduction to Database | 15 | 45 | – | 3 |
| CSCI313 | Introduction to Data-Structure and Algorithms | 15 | 45 | – | 3 |
| Math205 | Probability and Statistics I | 15 | 45 | – | 3 |
| DTSC301 | Introduction to Data Science | 15 | 45 | – | 3 |
| GE/DE | Elective II | 15 | 45 | – | 3 |
| Total | 15 | ||||
Second year – spring
| Code | Course Name | Nb of weeks | Nb of Lecture hours | Nb of labs hours | credits |
| COMP310 | Advanced Programming | 15 | 45 | – | 3 |
| CSCI315 | Web Application Development | 15 | 45 | 30 | 4(3; 1) |
| CSCI317 | Software Engineering | 15 | 45 | – | 3 |
| CSCI320 | Operating Systems | 15 | 45 | 30 | 4(3;1) |
| MATH250 | Numerical Computation and Analysis | 15 | 45 | – | 3 |
| Total | 17 | ||||
Second year – summer
| Code | Course Name | Nb of weeks | Nb of Lecture hours | Nb of labs hours | credits |
| GE / DE | Elective III | 8 | 45 | – | 3 |
| MATH305 | Probability and Statistics II | 8 | 45 | – | 3 |
| Total | 6 | ||||
Third year – fall
| Code | Course Name | Nb of weeks | Nb of Lecture hours | Nb of labs hours | credits |
| DTSC422 | Time series and statistical forecasting | 15 | 45 | – | 3 |
| CSCI410 | Artificial Intelligence and Machine Learning | 15 | 45 | – | 3 |
| DTSC420 | Introduction to Bayesian Data Analysis | 15 | 45 | – | 3 |
| MATH307 | Statistical Models | 15 | 45 | – | 3 |
| GE / DE | Elective IV | 15 | 45 | – | 3 |
| Total | 15 | ||||
Third year – spring
| Code | Course Name | Nb of weeks | Nb of Lecture hours | Nb of labs hours | credits |
| COMP415 | Design and Analysis of Algorithms | 15 | 45 | – | 3 |
| CSCI420 | Final Year Project | – | – | – | 3 |
| COMP412 | Advanced Databases | 15 | 45 | – | 3 |
| DTSC424 | Deep learning | 15 | 45 | – | 3 |
| Total | 12 | ||||
One credit is equivalent to 15 lecture hours or 30 laboratory hours per semester.
- Obtaining official Lebanese BACC II degree or any equivalent document.
- Conducting a placement test in Arabic Language and one of two foreign languages (English or French) , Informatics and Mathematics.
- Passing the academic orientation stage that determines the suitability of a student’s abilities and qualifications in accordance with the field of study.
