Online Syllabus

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

  • Read chapters 1-3 from "Java Fundamentals"

  • Complete online Java syntax exercises

2

Java Basics

  • Review variable declaration and data types

  • Write and execute simple Java programs

3

Object-Oriented Python

  • Study classes and objects in Python

  • Implement inheritance in Python programs

4

Introduction to C++

  • Explore basic syntax and control structures

  • Complete C++ coding challenges

5

Advanced Java Concepts

  • Dive into exception handling and file I/O

  • Work on Java project assignments

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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