College Computer Science Tutoring

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Computer science is a challenging subject, touching upon many different facets of computation. Students will be required to understand high level mathematics such as calculus, differential equations, and linear algebra. They will explore the theory and the practical applications of computing. They will take a peek into the problems that proliferated in the early years of technology, and they will learn high-demand problem solving, logical reasoning, and creative thinking skills that will allow them to tackle the issues we face today. Computer science is an exciting field! Every day, computer scientists are pushing the envelope on what is possible. 

It is challenging, but it is equally rewarding, and our tutors are here to help. 

Frequently Asked Questions

Why Tutoring By A College Professor?

Today, many students are required to take at least one CS course during their time in college, regardless of their major. Our tutors are excited to help both technical and non-technical students with their assignments. We have an incredible team of tutors who are industry professionals and/or champions of academia and are ready to begin scheduling to help with your computer science course. Please call 614-264-1110 today for a free consultation and sign up now.

How are tutoring sessions conducted?

Tutoring sessions are online on Zoom. You can tutor from the comfort of home or the bustle of a coffee shop. It’s up to you.

How long are most tutoring sessions?

Students typically tutor in 1 hour increments, but sessions can run as long as you need.

What if I need an emergency tutoring session for a test tomorrow?

Don’t hesitate to call us at 614-264-1110. We can have you connected with a tutor today to begin scheduling.

What Computer Science courses do you help with?

Please see below for a list of some of the Computer Science courses we’re familiar with.  If you do not see your student’s class listed below, we have likely still helped with the course previously and are still highly qualified to help-- our tutors are amazing experts in computer science.  Please call 614-264-1110 for more information.

Intro to Computer Science 

The Ohio State University: CSE 1110, CSE 1111, CSE 1112, CSE 1113, CSE 1114, CSE 1211, CSE 1213, CSE 1222, CSE 1223, CSE 1224

Purdue University: CS 18200, CS23500

University of Michigan: CSE 102, CSE 232

Indiana University: CSCI-A 591

Clemson University: CPSC 1010, CPSC 1020, 

University of Alabama: CS 100, CS 101, CS 104, 

Georgia Tech: CS 1301, CS 1331

Carnegie Mellon University: SCS 07-120, SCS 15-106, SCS 15-112

Washington University in St. Louis: CSE 131, CSE 132, 

Duke University: COMPSCI 101L, COMPSCI 102L 


Data Structures and Algorithms

The Ohio State University: CSE 2122, CSE 2123, CSE 2321, CSE 2331, CSE 2321

Purdue University: CS 25100, CS 38100

University of Michigan: CSE 260, CSE 331, CSE 431

Indiana University: CSCI-A 594, CSC1-B 403, CSCI-B 405

Vanderbilt University: CS 2201 , CS 2212, CS 3250

Clemson University: CPSC 2070, CPSC 2120, CPSC 3120

University of Alabama: CS 201, CS 470

Georgia Tech: CS 1332, CS 3510, CS 4520, CS 4530, CS 4540

Case Western Reserve University: CSDS 233, CSDS 310

Carnegie Mellon University: SCS 15-121, SCS 08-722, SCS 02-414, SCS 02-514, SCS 02-613, SCS 15-351, SCS 15-451, SCS 15-495

Washington University in St. Louis: CSE 247 

Duke University: COMPSCI 201, COMPSCI 330, COMPSCI 333


Computer Architecture 

The Ohio State University: CSE 2421, CSE 3421

University of Michigan: CSE 320, CSE 420

Indiana University: CSCI-B 443 

Vanderbilt University:CS 2281

Case Western Reserve University: CSDS 314

Carnegie Mellon University: SCS 15-213, SCS 15-346

Washington University in St. Louis: CSE 362M

Duke University: COMPSCI 250D

Database Management Systems

The Ohio State University: CSE 1114, CSE 3241, CSE 3244

Purdue University: CS 44800

University of Michigan: CSE 480

Clemson University: CPSC 4620  

University of Alabama: CS 301, CS 302, CS 305

Georgia Tech: CS 4400, CS 4420, CS 4423

Case Western Reserve University: CSDS 341

Carnegie Mellon University: SCS 15-415, SCS 15-445

Washington University in St. Louis: CSE 435S

Duke University: COMPSCI 316


Operating Systems

The Ohio State University: CSE 2431

University of Michigan: CSE 410

Clemson University: CPSC 3220

University of Alabama: CS 300

Georgia Tech: CS 3210, CS 4210

Case Western Reserve University: CSDS 338

Carnegie Mellon University: SCS 15-410

Washington University in St. Louis: CSE 422S, CSE 522S

Duke University: COMPSCI 310


Artificial Intelligence 

The Ohio State University: CSE 3521

Purdue University: CS 47100

University of Michigan: CSE 440

Indiana University: CSCI-B 351

Vanderbilt University: CS 4260

Clemson University: CPSC 4420 

University of Alabama: CS 465 

Georgia Tech: CS 3600

Case Western Reserve University: CSDS 391

Carnegie Mellon University: SCS 07-180, SCS 15-181, SCS 15-281, SCS 05-317  

Washington University in St. Louis: CSE 412A, CSE 513T, CSE 555T

Duke University: COMPSCI 370D


Machine Learning 

University of Michigan: CSE 404

Indiana University: CSCI-B 455

Vanderbilt University: CS 3262 

Clemson University: CPSC 4430 

University of Alabama: CS 484

Georgia Tech: CS 4641

Case Western Reserve University: CSDS 340

Carnegie Mellon University: SCS 10-301, SCS 10-315, SCS 10-335, SCS 10-405, SCS 10-418, SCS 02-620, SCS 05-434, SCS 17-634

Washington University in St. Louis: CSE 417T, CSE 513T, CSE 515T, CSE 517A, CSE 519T

Duke University: COMPSCI 371


Software Development / Software Engineering 

The Ohio State University: CSE 2221, CSE 2231 

Purdue University: CS30700

University of Michigan: CSE 435

University of Alabama: CS 200

Georgia Tech: CS 3300

Case Western Reserve University: CSDS 393

Carnegie Mellon: SCS 15-214, SCS 15-313

Washington University in St. Louis: CSE 437S, CSE 454A

Duke University: COMPSCI 307D, COMPSCI 308


Programming Languages 

The Ohio State University: CSE 2451, CSE 3341

Purdue University: CS 45600

University of Michigan: CSE 450

Indiana University: CSCI-A 597, CSCI-B 522

Vanderbilt University: CS 3270

University of Alabama: CS 403

Georgia Tech: CS 3240, CS 4392

Case Western Reserve University: CSDS 345

Washington University in St. Louis: CSE 425S, CSE 431S

Testimonials

See what Computer Science students and their parents say about their experience with Tutoring By A College Professor.  To search for testimonials by school, go to our Testimonials section at the top:

Computer Science Courses:

Intro to Computer Science

Common Topics in Intro to Computer Science: 

Intro to CS might include a high overview on various popular programming languages like Java, Python and C++. It might go over the pros and cons of different languages and their use cases. Concepts like Object-oriented programming, writing clean code, writing unit tests could be explored. Additional topics might include how to use a debugger, how to test your code, algorithm analysis and recursion.  

Here are some tips from our expert computer science tutors:

An Intro to CS course can cover a very large breadth of topics without going into too much detail. It will almost certainly include some programming. Popular introductory textbooks include:


Additionally, if you require supplementary learning material, Harvard offers a highly rated and well known online intro to CS course called CS50. It is self-paced and can be an incredible resource to help ease you into the world of computer science. 

Data Structures and Algorithms 

Common Topics in Data Structures and Algorithms 

A Data Structures and Algorithms course might include topics like basic data structures like arrays, Linked Lists, stacks, and queues. It could introduce you to the idea of algorithmic complexity. It could also explore topics such as divide-and-conquer algorithms, dynamic programming algorithms, network flow algorithms, linear and integer programming, large scale search algorithms, and NP-completeness. 


Here are some tips from our expert computer science tutors:

The Data Structures and Algorithms will be one of the most (if not the most) important classes you will take for your CS degree. Not only will it teach you about the tools in your problem solving toolbox, it is also material that you will likely see during coding interviews for internships and jobs. Take this class seriously. 

Leetcode is a popular website used to practice coding interview style questions. Leetcode offers its premium version at a discount for groups associated with universities. See if you can get a discount for Leetcode premium. It is immensely useful when preparing for interviews. 

Neetcode is a useful resource that provides explanations and solutions to coding interview style questions. 

Some popular books for this course are: 

Computer Architecture 

Common Topics in Computer Architecture

A Computer Architecture course might see topics like computer structure, assembly language, instruction execution, addressing techniques, digital representation of data. Additionally it might cover topics like computer system organization, logic design, microprogramming, cache and memory systems. 

Here are some tips from our expert computer science tutors:

A popular Computer Architecture textbook is Computer Architecture: A Quantitative Approach 

Database Management Systems

Common Topics in Database Management Systems 

Key topics in a Database class include data models, query languages (like SQL), storage architecture, indexing, transaction processing, recovery, query processing and parallel architecture. 

Here are some tips from our expert computer science tutors:

Structured Query Language (SQL) is a programming language used for storing and processing information in a relation database. SQL can be thought of as an umbrella term. In fact, there are several “SQL dialects” that are in use throughout industry. These include postgreSQL, mySQL, Oracle, SQL Server, etc. 

Relational vs non-relational databases 

Relational databases work with structured data. These are table and row oriented data. Non-relational databases do not have these constraints. These have no tables, rows, primary keys or foreign keys. Non-relational databases, however, have the ability to store a large amount of data and provide scalability and flexibility when meeting changing business requirements. 

Operating Systems

Common Topics in Operating Systems 

An OS course might cover topics like the process model, virtual memory, threads, synchronization and deadlock. It might cover higher level topics such as file systems, interprocess communication, networking, and security. 


Artificial Intelligence

Common Topics in Database Management Systems 

An AI course might explore topics like algorithms for search and planning, optimization, reasoning and inference mechanisms, machine learning, deep learning and neural networks, natural language processing, computer vision. 

Here are some tips from our expert computer science tutors:

Artificial intelligence is a very broad umbrella term. In fact, LLMs (large language models) like chatGPT that have become popular recently represent a subset of the field of artificial intelligence. Machine Learning, Deep Learning and Reinforcement Learning all exist under the umbrella term “AI.” However, in industry, the terms AI and ML are used almost interchangeably.

A popular textbook for AI is Artificial Intelligence: A Modern Approach.

Machine Learning 

Common Topics in Machine Learning

An ML course might include topics like supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines), unsupervised learning (clustering, dimensionality reduction, kernel methods), learning theory and adaptive control. Other topics might include perceptrons, logistic regression, decision trees, Bayesian learning, neural networks and backpropagation. 

Here are some tips from our expert computer science tutors:


Supervised learning vs Unsupervised learning

One of the most important topics taught in an ML class is the difference between supervised and unsupervised learning. These represent different ways a model can be trained. To put simply, supervised learning uses labeled training data while unsupervised learning does not. 

Supervised learning uses labeled data to train itself to make predictions. With supervised learning, the model is iteratively adjusting itself to minimize error. Unsupervised learning will work independently of labels to learn the data’s inherent structure without any guidance or instruction of what is “correct.”

A popular textbook for ML is Deep Learning by Ian Goodfellow.

Software Development/Software Engineering 

Common Topics in Software Development/Software Engineering

A software development/engineering course could touch upon the software development lifecycle. This includes developing, delivering, and maintaining software products. You could learn basic development skills, common terminology used in industry, traditional coding standards/guidelines, techniques in modifying, building and testing software.


Here are some tips from our expert computer science tutors:

Some popular textbooks for this course are 

Programming Languages 

Common Topics in Software Development/Software Engineering:

Typical topics in a Programming Languages course might include language design tradeoffs; implementation considerations; functional, imperative and object-oriented paradigms; formal semantic methods and program analysis; higher order functions and closures; runtime support for language features; security issues

Here are some tips from our expert computer science tutors:

A popular textbook used in Programming Languages courses is Programming Language Pragmatics by Michael Scott.


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