Online Syllabus
Online Course
Course Title | [COURSE TITLE] |
Course Code | [COURSE CODE] |
Instructor Name | [YOUR NAME] |
Email | [YOUR EMAIL] |
Office Hours | [OFFICE HOURS] |
Class Location | [CLASS LOCATION] |
Class Time | [CLASS TIME] |
Class Duration | [DATE] - [DATE] |
I. Course Description
Offered by [YOUR COMPANY NAME], this course provides an introductory overview of computer science. It covers fundamental concepts such as programming languages, algorithms, data structures, and basics of artificial intelligence. This course is designed for beginners with little to no prior programming experience.
II. Instructor Information
Instructor's name: [YOUR NAME]
Contact email: [YOUR EMAIL]
III. Learning Objectives
Understand the basics of various programming languages including Java, Python, and C++.
Develop problem-solving skills using algorithms and data structures.
Apply principles of software development in practical projects.
Understand basics of Artificial Intelligence and Machine Learning.
Appreciate complexities and ethics of computer science applications in real world.
IV. Course Schedule
Week | Topic | Assignment |
|---|
1 | Introduction to Java | |
2 | Java Basics | |
3 | Object-Oriented Python | |
4 | Introduction to C++ | |
5 | Advanced Java Concepts | |
V. Required Reading and Materials
Course Textbook: "Computer Science: An Overview" by J. Glenn Brookshear and Dennis Brylow.
Recommended Reference: "Introduction to Algorithms" by Thomas H. Cormen.
"Introduction to Java Programming" by Y. Daniel Liang.
Online resource: Codecademy Python course.
Recommended Resource: "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig.
VI. Assignments and Assessments
Programming assignments to be submitted via email.
Mid-term examination on programming and algorithms.
Final project that requires the application of learned concepts.
A comprehensive final examination.
Participation in discussion forums will also be counted.
VII. Course Policy
Assignments are due on the designated date by 11:59 PM (ET). Late submissions will be marked down.
All students are expected to actively engage in course discussions and forums.
Academic integrity will be strictly enforced. Any form of plagiarism will not be tolerated.
All communications should be respectful and professional.
Any issues related to course material or assignments should be communicated early and addressed promptly.
VIII. Grading Policy
Criteria | Percentage |
|---|
Assignments | 30% |
Mid-Term Examination | 20% |
Final Project | 20% |
Final Examination | 20% |
Participation | 10% |
Total | 100% |
Disclaimer
The provided course outline is designed to inform and guide the flow and framework of this course. Nevertheless, it should be emphasized that the outline is flexible and may undergo small or significant modifications based on the instructor's professional judgement, discretion and potentially, time constraints or student needs. If changes are made, we guarantee timely and effective communication to all course participants. This is in an effort to keep everyone well-versed and in sync with any modifications to the course framework.
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