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For more details or admissions contact now!
Andrew Barrow
Head of Admission Department
Accreditation
The Higher Secondary Certificate (HSC) in Data Science provides students with a strong foundation in data analysis, machine learning, and programming. This program integrates core academic subjects with specialized training in Python programming, data analytics, statistical methods, and machine learning models.Designed over four semesters, this program equips students with analytical and problem-solving skills, preparing them for higher education in data science, artificial intelligence, or computer science. Through a combination of theoretical knowledge and hands-on projects, students will gain practical experience in data-driven decision-making.
The HSC in Data Science aims to:
- Introduce students to fundamental data science concepts, including Python programming, statistics, and data analytics.
- Develop problem-solving skills through hands-on projects in machine learning, data visualization, and data privacy.
- Equip students with the knowledge of regression models, clustering techniques, and decision trees to analyze real-world datasets.
- Prepare students for higher education in data science, artificial intelligence, and data engineering.
- Build a strong foundation for careers in data analysis, machine learning, and software development.
This program is an excellent pathway for students looking to pursue a Bachelor’s degree in Data Science, Computer Science, or AI, offering a comprehensive introduction to the field of data-driven technology.
Road Map |
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|---|---|---|---|
Year 1 - Semester 1 |
|||
| Core Units | Credits | ||
| English | 1 | ||
| Algebra I | 1 | ||
| US History | 1 | ||
| DS Subjects | |||
| The Field of Data Science | 0.5 | ||
| Python for Data Science | 1 | ||
| Creating and Interpreting | 1 | ||
| Data and Descriptive Statistics in Data Science | 0.5 | ||
Semester 2 |
|||
| Core Units | Credits | ||
| English 2: Language Skills | 1 | ||
| Geometry | 1 | ||
| World History | 1 | ||
| General Science | 1 | ||
| DS Subjects | |||
| Fundamentals of Data Analytics | 0.5 | ||
| Data Analytics with Python | 1 | ||
| Machine Learning Methods and Models in Data Science | 0.5 | ||
Year 2 - Semester 3 |
|||
| Core Units | Credits | ||
| English 3: Composition | 1 | ||
| Algebra II | 1 | ||
| Government / Civics | 1 | ||
| DS Subjects | |||
| The Machine Learning Process | 1 | ||
| Linear Regression in Data Science | 0.5 | ||
| Logistic Regression in Data Science | 0.5 | ||
| K-means Clustering in Data Science | 1 | ||
Semester 4 |
|||
| Core Units | Credits | ||
| English 4: Critical Thinking | 1 | ||
| Pre Calculus | 1 | ||
| Economics | 1 | ||
| Environmental Science | 1 | ||
| DS Subjects | |||
| Decision Trees in Data Science | 0.5 | ||
| Synthetic Data for Privacy and Security in Data Science | 1 | ||
| Graphs and Graph Data Science | 0.5 | ||
For more details or admissions contact now!
Andrew Barrow
Head of Admission Department