Spesialisasi dan variasi
Informasi lain yang dikumpulkan
Persyaratan Program Kategori Kursus Kategori kursus berikut digunakan untuk mendefinisikan persyaratan program dalam program Sarjana Ilmu Data. Mata Kuliah Pilihan Bebas Semua mata kuliah yang ditawarkan oleh Fakultas Seni dan Ilmu Sosial, Fakultas Urusan Publik dan Global, Sprott School of Business dan Fakultas Sains kecuali untuk mata kuliah dalam kategori Mata Kuliah Terlarang. Mata kuliah pilihan bebas dapat mencakup mata kuliah COMP, CSEC, DATA, MATH dan STAT. Mata Kuliah Terlarang Mata kuliah berikut tidak dapat digunakan untuk kredit dalam B.D.S. Harap dicatat bahwa setiap mata kuliah yang tercross-listing dengan yang ada dalam daftar juga dilarang : BIOL 3604 [0.5] Statistics for Biologists BUSI 1401 [0.5] Foundations of Information Systems BUSI 2401 [0.5] Introduction to Data Analytics BUSI 2402 [0.5] Business Applications Development BUSI 3400 [0.5] Database Design CGSC 1005 [0.5] Computational Methods in Cognitive Science COMP 1001 [0.5] Introduction to Computational Thinking for Arts and Social Science Students COMS 3001 [0.5] Quantitative Research in Communication CRCJ 3001 [0.5] Quantitative Methods in Criminology ECON 1401 / MATH 1401 [0.5] Elementary Mathematics for Economics I ECON 1402 / MATH 1402 [0.5] Elementary Mathematics for Economics II ECON 2210 [0.5] Introductory Statistics for Economics ECON 3001 [0.5] Mathematical Methods of Economics ECON 4001 [0.5] Mathematical Analysis in Economics ECON 4002 [0.5] Statistical Analysis in Economics ECON 4004 [0.5] Operations Research: Linear Programming Models ECON 4706 [0.5] Econometrics I ECON 4707 [0.5] Econometrics II ECON 4713 [0.5] Time-Series Econometrics GEOG 2006 [0.5] Introduction to Quantitative Research ECOR 2606 [0.5] Numerical Methods GEOG 3003 [0.5] Quantitative Geography MATH 1009 [0.5] Mathematics for Business MATH 1119 [0.5] Linear Algebra: with Applications to Business NEUR 2001 [0.5] Introduction to Research Methods in Neuroscience NEUR 2002 [0.5] Introduction to Statistics in Neuroscience NEUR 3001 [0.5] Data Analysis in Neuroscience I NEUR 3002 [0.5] Data Analysis in Neuroscience II PSCI 2702 [0.5] A Statistical Toolkit for Political Scientists PSYC 2001 [0.5] Introduction to Research Methods in Psychology PSYC 2002 [0.5] Introduction to Statistics in Psychology PSYC 3000 [1.0] Design and Analysis in Psychological Research SOCI 2004 [0.5] Data Literacy for Social Sciences SOCI 3008 [0.5] Data Analysis for Social Sciences SOCI 4102 [0.5] Multiple Regression Analysis SOWK 3001 [0.5] Introduction to Research Methods in Social Work SYSC 2510 [0.5] Probability, Statistics and Random Processes for Engineers all 0000-level courses and all courses in BIT, IMD, IRM, MPAD, NET, OSS, PLT and ITEC except for the following: BIT 1000 , BIT 1001 , BIT 1100 , BIT 1101 , BIT 1200 , BIT 1201 , BIT 2000 , BIT 2004 (no longer offered), BIT 2005 (no longer offered), BIT 2007 (no longer offered), BIT 2100 (no longer offered), BIT 2300 (no longer offered), MPAD 2400 , MPAD 2501 (no longer offered), MPAD 3300 , MPAD 3501 , MPAD 4001 , MPAD 4501 , MPAD 4502 , MPAD 4503 , MPAD 4504 . Data Science B.D.S. Honours (20.0 kredit)
Jalur dan ketentuan program
Tabel-tabel ini mencantumkan persyaratan dari sumber untuk periode yang ditunjukkan. Interpretasi resmi merupakan kewenangan universitas.
Jalur 1
| A. Kredit yang Dimasukkan dalam IPK Utama (13,5 kredit) | ||
| 1. 1.5 kredit dalam: | 1.5 | |
| MATH 1007 [0.5] | Kalkulus Dasar I | |
| MATH 1104 [0.5] | Linear Algebra for Engineering or Science | |
| MATH 2007 [0.5] | Kalkulus Dasar II | |
| 2. 1.0 kredit dalam: | 1.0 | |
| DATA 3200 [0.5] | Keterampilan Komunikasi untuk Ilmuwan Data | |
| PHIL 2106 [0.5] | Etika Informasi | |
| 3. 5.5 kredit dalam: | 5.5 | |
| COMP 1405 [0.5] | Pengantar Ilmu Komputer I | |
| COMP 1406 [0.5] | Pengantar Ilmu Komputer II | |
| COMP 1805 [0.5] | Discrete Structures I | |
| COMP 2109 [0.5] | Pengantar Keamanan dan Privasi | |
| COMP 2401 [0.5] | Pengantar Pemrograman Sistem | |
| COMP 2402 [0.5] | Tipe Data Abstrak dan Algoritma | |
| COMP 2404 [0.5] | Pengantar Rekayasa Perangkat Lunak | |
| COMP 2406 [0.5] | Fundamentals of Web Applications | |
| COMP 2804 [0.5] | Discrete Structures II | |
| COMP 3105 [0.5] | Introduction to Machine Learning | |
| COMP 4107 [0.5] | Jaringan Saraf | |
| 4. 2.0 kredit dalam: | 2.0 | |
| DATA 1517 [0.5] | Pemodelan Data I | |
| DATA 1519 [0.5] | Pemodelan Data II | |
| DATA 2500 [0.5] | Pengolahan Data di R | |
| DATA 3500 [0.5] | Pemrograman Statistik di R | |
| 5. 2.0 kredit dalam: | 2.0 | |
| STAT 1500 [0.5] | Pengantar Komputasi Statistik | |
| STAT 2210 [0.5] | Dasar-dasar Ilmu Data Inferensial I | |
| STAT 3553 [0.5] | Pemodelan Regresi (Honours) | |
| STAT 4601 [0.5] | Penambangan Data I (Honours) | |
| 6. 1.0 kredit dari: | 1.0 | |
| COMP 4010 [0.5] | Pengantar Pembelajaran Penguatan | |
| COMP 4102 [0.5] | Visi Komputer | |
| COMP 4115 [0.5] | Pengantar Pengolahan Bahasa Alami | |
| COMP 4116 [0.5] | Sistem Multiagen |
Mata kuliah
Mata kuliah ini ditemukan di halaman sumber program. Kehadirannya tidak berarti semuanya wajib di setiap jalur studi.
Sumber dan referensi
Tahun acuan : 2026-27
Tanggal dan sumber disimpan untuk membantu Anda memverifikasi informasi. Terjemahan disediakan untuk memudahkan pembacaan; sumber resmi menjadi rujukan untuk syarat dan ketentuan.
Referensi sumber : https://calendar.carleton.ca/undergrad/undergradprograms/datascience/