Kursus TVET
Data Sains

MCU-1-11

Pengenalan Kursus

Turn data into decisions. Deploy production-grade models.

This part-time bootcamp takes you from zero to building real analyses and machine learning models—without leaving your full-time job. Over 14 weeks, you’ll learn by doing: cleaning messy spreadsheets and CSVs, visualising meaningful trends, validating ideas with simple statistics, pulling fresh data via APIs or web scraping, and building models for classification, regression, and clustering. You’ll also step into deep learning, complete a portfolio-ready capstone project, and finish with a proctored final exam. Graduate with a government-recognised, accredited certificate that proves you can turn raw data into real results.

Maklumat Latihan TVET

Tahap Pengajian
Diploma Kemahiran Malaysia / Diploma Tahap 4 / Diploma Setaraf

Syarat Kelayakan
1. 3M - Membaca menulis dan mengira
1.1
1. Boleh Membaca, Menulis dan Mengira (Wajib)

Dan

2. Kelayakan Akademik
2.1

Tiada Pendidikan Formal Atau Mempunyai Minat, Boleh Membaca Dan Menulis


Dan

3. Umur
3.1

Umur Minimum : 16
Umur Maksimum : 45


Tempoh Pengajian
4 Bulan

Prospek Kerjaya
Data Analyst, Business Analyst, Product Analyst, IT System Analyst, Data Analyst, Consultant, Marketing Analyst

Butiran Penyedia Latihan TVET

Nama Institusi
FORWARD COLLEGE
Alamat
NO.2, LEBUH ACHEH,
GEORGETOWN,
Negeri
PULAU PINANG
Penyelaras
TEOH LAY PIN
Telefon
0124091682
Emel
hello@forward.edu.my
Laman Web
https://forward.edu.my/

Lain-lain Maklumat

Lain-lain Maklumat Berkaitan
Learning Outcomes
- Master Python for real data work – write clean, reusable code, handle spreadsheets, and use Pandas & NumPy for fast data analysis.
- Prepare & explore real-world data – clean messy datasets, extract data via APIs/web scraping, and create story-ready visuals.
- Make statistics your superpower – summarise trends, test hypotheses, and make data-driven decisions confidently.
- Build machine learning that matters – train and evaluate models for real business problems.
- Step into deep learning – understand neural networks using Keras/TensorFlow and when to apply them effectively.


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