This course will be offered asynchronous online, with synchronous instructor sessions via zoom weekly for Q&A or other assistance with coursework. The course concludes with a final exam. Successful completion includes testing on the certificate course content with 85% or better score. Certificates of completion will be issued to students who successfully complete the course, to be included with any CIT graduate program admissions materials. 

Contact

The instructor for this course is Sana Neji (sananeji@umich.edu).

Textbook

Deitel, P. J., & Deitel, H. M. (2017). Java: How to program: Late Objects. New York, NY: Pearson.

Software

https://netbeans.apache.org/download/index.htmlLinks to an external site. (Netbeans) 

or you can use Repl.it environmentLinks to an external site.

Description

Introduction to problem-solving and programming principles appropriate for scientific and technical applications. Development of step-wise refinement and program decomposition methods. Programming language concepts including iteration, selection, input-output protocols, arrays, structures, and subprograms. The programming language used is Java. In addition, this course will introduce the students to the principles of computer analysis of problems, design of algorithms, programming, and testing using the Java programming language. Topics include problem analysis basics of programming, inheritance, complexity, data structures, linked lists, stacks, queues, trees recursion, and the mechanics of running, testing, and debugging.

Topic Details

Week 1 - Algorithmic Analysis

• Design algorithms using pseudo-code

• Use object-oriented programming methods to create computer validity programs that solve a variety of problems

• Model multiple algorithmic solutions to computing problems and compare them

• Assess different algorithmic approaches to optimization, performance, and accuracy

Week 2 - Object-oriented Design

• Classes and objects

• Inheritance and polymorphism

Week 3: Data structures

• Primitive data structures such as integers, floating-point numbers, characters and booleans

• Non-primitive data structures such as arrays, linked lists, stacks, queues, trees, graphs and hash tables

Week 4: Complexity Analysis

• Sorting algorithms

• Recursion

• Complexity of Sorting Algorithms

Final exam