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| Course Name | Course Syllabus | Relevant the Best (Mature) Book | Online Course |
|---|---|---|---|
| Introduction to Computing System | Basics of computing, hardware, software, and operating systems | "Computer Organization and Design" by David A. Patterson and John L. Hennessy | TODO |
| AI in Industry 4.0 | AI applications in smart manufacturing and Industry 4.0 | "Artificial Intelligence: A Guide to Intelligent Systems" by Michael Negnevitsky | TODO |
| Algorithm | Fundamental algorithms and their analysis | "Introduction to Algorithms" by Thomas H. Cormen et al. | TODO |
| Introduction to Data Analytics | Basics of data analysis, data cleaning, and visualization | "Data Science for Business" by Foster Provost and Tom Fawcett | TODO |
| Data Visualization | Techniques and tools for effective data visualization | "Storytelling with Data" by Cole Nussbaumer Knaflic | TODO |
| Introduction to Machine Learning | Basics of machine learning, supervised and unsupervised learning | "Pattern Recognition and Machine Learning" by Christopher M. Bishop | TODO |
| Deep Learning | Neural networks, backpropagation, and advanced deep learning techniques | "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville | TODO |
| Operating Systems | Concepts of operating systems, processes, and memory management | "Operating System Concepts" by Abraham Silberschatz, Peter B. Galvin, and Greg Gagne | TODO |
| Autonomous Vehicle | Technologies and algorithms for autonomous vehicles | "Autonomous Driving: How the Driverless Revolution will Change the World" by Andreas Herrmann | TODO |
| Field Practice x4 | Practical experience in a real-world setting (Co-op program or internship) | N/A | N/A |
| Linear Algebra | Vectors, matrices, and linear transformations | "Linear Algebra and Its Applications" by Gilbert Strang | Khan Academy: Linear Algebra |
| Statistics | Probability, statistical inference, and data analysis | "Statistics for Engineers and Scientists" by William Navidi | TODO |
| Data Structure | Data organization, storage, and retrieval | "Data Structures and Algorithms in Python" by Michael T. Goodrich et al. | TODO |
| Freshman Capstone Project | A project integrating knowledge from freshman year courses | N/A | N/A |
| Essential Mathematics for AI | Mathematical foundations for AI and machine learning | "Mathematics for Machine Learning" by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong | TODO |
| SW Engineering | Software development lifecycle, design patterns, and best practices | "Software Engineering: A Practitioner's Approach" by Roger S. Pressman | TODO |
| Computer Networks | Networking principles, protocols, and architectures | "Computer Networking: A Top-Down Approach" by James F. Kurose and Keith W. Ross | TODO |
| Database | Database design, SQL, and data management | "Database System Concepts" by Abraham Silberschatz, Henry F. Korth, and S. Sudarshan | TODO |
| Big Data Platform | Technologies and tools for handling big data | "Big Data: Principles and Best Practices of Scalable Real-Time Data Systems" by Nathan Marz | TODO |
| Web Analytics | Techniques for analyzing web data and user behavior | "Web Analytics 2.0" by Avinash Kaushik | TODO |
| Principles of Blockchain Technology | Blockchain fundamentals, cryptography, and decentralized applications | "Mastering Blockchain" by Imran Bashir | TODO |
| Advanced Big Data Tools | Advanced tools and techniques for big data processing | "Hadoop: The Definitive Guide" by Tom White | TODO |
| Cloud Platform | Cloud computing concepts, services, and architectures | "Cloud Computing: Concepts, Technology & Architecture" by Thomas Erl | TODO |
| Natural Language Processing | Techniques for processing and analyzing human language data | "Speech and Language Processing" by Daniel Jurafsky and James H. Martin | TODO |
| Computer Vision | Image processing, object detection, and recognition | "Computer Vision: Algorithms and Applications" by Richard Szeliski | TODO |
| Capstone Project 1 | A comprehensive project integrating knowledge from multiple courses | N/A | N/A |
| Capstone Project 2 | A continuation and expansion of Capstone Project 1 | N/A | N/A |
| Information Security in Industry 4.0 | Security challenges and solutions in Industry 4.0 | "Cybersecurity and Cyberwar: What Everyone Needs to Know" by P.W. Singer and Allan Friedman | TODO |
| Cognitive Science | Study of the mind, intelligence, and behavior | "Cognitive Science: An Introduction to the Study of Mind" by Jay Friedenberg and Gordon Silverman | TODO |
| AI in Digital Healthcare | AI applications in healthcare and medical data analysis | "Artificial Intelligence in Healthcare" by Tom Lawry | TODO |
| Internship x4 | Practical experience in a professional setting | N/A | N/A |
Mana bu semester bu fanni ol deyish sal xato bo'lishi mumkin axir baxorda yoki kuzda kelgan bolalarning biriinchi semesterlarida xar xil bo'ladi. Shunga bir pog'ona teparoq. 1 yil shuni olishga harakat qil, 2 yil bu, 3 yili nima qilish, 4 yili nima qilish.
Iymon muhimligi va bu yo'l allaqachon bosilib bo'lgan. Bizni o'zimiz xarakat qilmagunimizcha kech kim o'zgartirmaydi. Hard in training, easy in battle. Qanday ko'rinishda qilsak, o'qishga oson bo'ladi? Bir faraz qilaylikchi.
Har bir fan, o'zini syllabusi, maslahati, taluqli kitob, online kurs va imtihon sifat mashq. Masalan bunday yoki unday vazifa (proyektlar) Qo'shimcha kurslar, masalan Git bilan ishlash, OOP fanlari, yoki C yoki C++, yoki Interpreneurship, System Design, ML yoki backend yoki front-endga oid.
Qo'yidagi fanlarni olishga harakat qil:
- Programming language, algorithms, Introduction to Computing systems, Linear Algebra
- OOP,
- Databases
- Computer Networks
- Computer Security
- Final capstone project
- Deep Learning yokki Machine Learning yoki Computer Vision yoki NLP (agar qiziqsa)
- Cloud computing
- Advanced Big Data
- Internship ( Co-op program)
- Universal 18 credits per semester (36 credits for 2 semesters)
Qaysi fan? Ish topshirish Ilm kamroq bo'lsa mustaxkamlash Bakalavrdagi fanlar yordan tegar
Thesis qilish ?
- Ilm olish pok va halol yo‘l. Uni hurmat qiling, so‘rashdan tortinmang.
- Kitob o‘qish ibodatga o‘xshaydi. O‘z ustingizda ishlang.
- Doimiy harakat qiling. Agar tushunmasangiz, so‘rang, izlaning.
- Maqsadingizni esdan chiqarmang. Har doim o‘z yo‘lingizni belgilab boring.
- Uyqu va vaqtni boshqaring. 6-7 soat uxlash yetarli.
- Faol o‘rganing. Harakat qilib, fikrlab, savollar berib o‘rganing.
- Portfolio va CV ustida ishlang. Bu sizning kelajakdagi muvaffaqiyatingiz kaliti.
Tabriklaymiz six Bakalavr yoki Magistratura equivalent darajada tamomladingiz! Faqat oldinga! Kuch birlikda! Fikringizni ulashing yoki uxshu qo'llanmaga xissa qo'shing.
- 커피 상회 - 대전 동구 동대전로 200 자양동 197-6
- Coffeenie - Coffeenie 162, Dongdaejeon-ro, Dong-gu, Daejeon
- Beanie Coffee - 대전 동구 동대전로 225 자양동 198-16
- 머물다가게 - 머물다가게 39, Dongdaejeon-ro 154beon-gil, Dong-gu, Daejeon
- Koreada kofeni o'rtacha nrxi 5000KRW, va deyarli hamma coffee shoplarda kofe olishingiz shart!!!
- Albatta Uyda ham dars qilishingiz mumkin :)