After listening to a Degree of Freedom podcast recently, I discovered this site called Degreed, and I am hooked. Degreed is a site where you can display all of your education including MOOCs, books read, University degrees, events attended, and videos watched. Most of the business and education world put so much emphasis on the formal education that one has received, but disregard other educational experiences that contribute to each individual’s knowledge.
While I am excited to get started building my profile, I am most excited about a feature they offer called “Pathways.” Pathways are specific tracks of study that compile an entire sequence of courses for you from a chosen field from MOOC providers that are the equivalent to a traditional degree program. In the Computer Science pathway, each section of classes is divided into categories including Math, Theory of Computer Science, Computer Security, and Machine Learning. I will definitely be using this as a guide for studying in the field of Computer Science.
Here is the curriculum laid out for the Computer Science Pathway:
Computer Science Level 1 Pathway:
Introduction to Computer Science
— Lesson 1: Programming (An Introduction to Interactive Programming in Python)
— Lesson 2: Principles of Computing (Principles of Computing)
— Lesson 3: Algorithmic Thinking (Algorithmic Thinking)
Foundations of Computer Science
— Lesson 1: Computer Architecture (The Hardware/Software Interface)
— Lesson 2: Computer Networks (Computer Networks)
— Lesson 3: Design and Analysis of Algorithms (Algorithms: Design and Analysis, Part 1 & Algorithms: Design and Analysis, Part 2)
Math
— Lesson 1: Calculus (Calculus One & Calculus Two: Sequences and Series)
— Lesson 2: Statistics (Introduction to Probability – The Science of Uncertainty)
— Lesson 3: Linear Algebra (Linear Algebra – Foundations to Frontiers)
Science
— Lesson 1: Physics (Intro to Physics)
— Lesson 2: Electricity and Magnetism (Electricity & Magnetism)
— Lesson 3: Electronics (Circuits and Electronics)
Computer Science Level 2 Pathway:
Theory of Computer Science
— Lesson 1: Automata (Automata)
— Lesson 2: Compilers (Compilers)
— Lesson 3: Analysis of Algorithms (Analysis of Algorithms & Analytic Combinatorics)
— Lesson 4: Quantum Computing (Quantum Mechanics and Quantum Computation)
Applied Computer Science
— Lesson 1: Databases (Introduction to Databases)
— Lesson 2: Parallel Programming (Heterogeneous Parallel Programming)
— Lesson 3: Embedded Systems (Embedded Systems – Shape the World)
Computer Security
— Lesson 1: Cryptography (Cryptography I & Cryptography II)
— Lesson 2: Computer Security (Computer Security)
Machine Learning
— Lesson 1: Machine Learning (Machine Learning)
— Lesson 2: Natural Language Processing (Natural Language Processing)
— Lesson 3: Probabilistic Graphical Models (Probabilistic Graphical Models)