Tasheel

Master in Data Science (By Coursework & Project)

Course Name:

Master in Data Science (By Coursework & Project)

University Name:

Universiti Tenaga Nasional (UNITEN)

Campus:

Putrajaya

Qualification:

Master

Duration:

1 years

Intake:

January, July, September

IELTS:

6.0

Study Mode:

On-campus

Study Type:

Full time study

Program Mode:

Mixed Mode

Yearly Tuition Fees body { font-family: Poppins, sans-serif; margin: 0; padding: 0; background-color: #f5f5f5; } .table-container { width: 100%; /* Full width of the container */ background-color: #fff; border-radius: 8px; overflow: hidden; border: 1px solid #ddd; } .table-header { background-color: #16726F; color: white; padding: 12px; text-align: center; font-size: 18px; font-family: 'Lexend', sans-serif; } table { width: 50%; /* Table takes up 100% width */ border-collapse: collapse; } th, td { padding: 12px; text-align: left; border-bottom: 1px solid #ddd; } th { background-color: #585858; color: #585858; } tr:hover { background-color: #f2f2f2; } td { color: #585858; } .table-row-first th { color: #585858; } /* Make the table responsive */ @media (max-width: 768px) { .table-container { width: 100%; /* Full width on smaller screens */ padding: 10px; } th, td { font-size: 14px; /* Adjust text size for smaller screens */ padding: 8px; /* Reduce padding for better fitting */ } }
Yearly Tuition Fees
Year Fee
1st Year MYR 37,000
Other Fees body { font-family: Poppins, sans-serif; margin: 0; padding: 0; background-color: #f5f5f5; } .table-container { width: 100%; background-color: #fff; border-radius: 8px; overflow: hidden; border: 1px solid #ddd; } .table-header { background-color: #16726F; color: white; padding: 12px; text-align: center; font-size: 18px; font-family: 'Lexend', sans-serif; } table { width: 100%; border-collapse: collapse; } th, td { padding: 12px; text-align: left; border-bottom: 1px solid #ddd; } th { background-color: #585858; color: #585858; } tr:hover { background-color: #f2f2f2; } td { color: #585858; } .table-row-first th { color: #585858; }
Other Fees
Category Fees
Application Fee MYR 1,100
EMGS Application Fee (Visa) MYR 2,850
Registration Fee MYR 7,000
Note:

+University fees for this course do not include 6% tax (SST)

Campus

Putrajaya

Qualification

Master

Duration

1 years

Intake

January, July, September

IELTS

6.0

Study Mode

On-campus

Study Type

Full time study

Program Mode

Mixed Mode

Are you interested to apply for

Universiti Tenaga Nasional (UNITEN)?

Course Fee for International Students

Yearly Tuition Fees
Yearly Tuition Fees
Year Fee
1st Year MYR 37,000
Other Fees
Other Fees
Category Fees
Application Fee MYR 1,100
EMGS Application Fee (Visa) MYR 2,850
Registration Fee MYR 7,000
Note:

+University fees for this course do not include 6% tax (SST)

The Master in Data Science (By Coursework & Project) at UNITEN (Universiti Tenaga Nasional) is the ultimate degree for the “modern fortune teller.” It is designed for those who want to master the art of predicting the future using data. This program transforms you from a number-cruncher into a Data Storyteller. You won’t just learn dry statistics; you will master the industry-standard tools—Python, Advanced Machine Learning, and Data Visualization—to turn complex chaos into clear, actionable business strategies. The curriculum is highly flexible, allowing you to specialize in cutting-edge fields like Natural Language Processing (NLP) (building chatbots) or Data Governance (managing corporate data strategy). The final project ensures you graduate not just with a degree, but with a proven portfolio of solving real-world problems.
Programme Structure
Programme Structure
Category Subjects
Semester I
  • Data Analytics
  • Advanced Machine Learning
  • Algorithms and Programming in Python
  • Elective 1
  • Research Methodology
Semester II
  • Advanced Data Visualisation
  • Advanced Text Analytics
  • Elective 2
  • Elective 3
  • Project
Semester III
  • Project
Elective Subjects (Choose 3)
  • Data Governance
  • Advanced Project Management
  • Natural Language Processing
  • Reinforcement Learning
Notes

The project spans Semesters II and III, with submission and evaluation in Semester III.

N/A
Based on MYR
Exchanged Amount is:
0