Computer Engineering Principles and Computational Thinking Study Guide

Course Structure, Grading Policies, and Academic Regulations

• Assessment & Grading Allocation:

  • Quizzes: $15\%$ of the total course grade.

  • Midterm Examination: $40\%$ of the total course grade.

  • Final Examination: $40\%$ of the total course grade.

  • Attendance: $5\%$ of the total course grade.

• Quiz Requirements & Parameters:

  • Format: Quizzes are strictly closed-book. Daily and weekly slide review is mandatory to succeed.

  • Frequency: Administered almost every week based on the material covered in the previous week's lecture slides.

  • Question Structure: Contains $3$ to $6$ questions consisting of multiple-choice, true/false, or a combination of both.

• Midterm and Final Examination Parameters:

  • Format: Exams are open-book.

  • Question Structure: Consists of $30$ to $50$ questions, composed of multiple-choice and true/false items.

  • Curricular Scope:

    • Midterm Exam: Covers Chapter 1 through Chapter 6.

    • Final Exam: Covers Chapter 7 through Chapter 12 (non-cumulative; does not include Chapters 1 through 6).

  • Time Duration: Administered during the full scheduled class period, from $02:30\text{ PM}$ to $04:10\text{ PM}$.

• Attendance, Lateness, and Attendance Policy:

  • Sign-In Requirement: Mandatory physical sign-in sheet upon arrival in class.

  • Lateness Window: Arrival $5$ to $10\text{ minutes}$ past class start time is tolerable; arriving beyond this window is marked late.

  • Absence Equivalency: Every $2$ recorded latenesses equal $1\text{ official absence}$.

  • Institutional Absence Threshold: CUNY permits a maximum of $2$ absences per semester. Exceeding this limit severely impacts the final grade due to missed quizzes and examinations.

• Grading Scale Breakdown:

  • $93 - 100$: A

  • $90 - 92.9$: A-

  • $87 - 89.9$: B+

• Classroom Policies & Slide Content:

  • Mobile Devices: Must be placed on silent mode. Emergency or important family calls may be answered by stepping outside the room.

  • Slide Volume: Weekly presentation decks vary in length, spanning anywhere from $40$, $50$, $60$, to $80$ slides per topic.

Fundamentals of Computer Engineering and Major Specializations

• Definition of Computer Engineering:

  • An interdisciplinary field integrating Computer Science (CS) and Electrical Engineering (EE) necessary for developing computer hardware and software systems.

  • Encompasses overarching Information Technology (IT) disciplines.

• Core Branches of Computer Engineering:

  1. Hardware Engineering

  2. Software Engineering

  3. Network Engineering

• Prerequisite Physics Requirements:

  • Calculus-Based Physics Track: Calculus-based Physics I and Calculus-based Physics II are required for students planning to pursue a Master's degree or advanced graduate research.

  • Algebra-Based Physics Track: Algebra-based Physics I and Algebra-based Physics II are sufficient only for students terminating their education at a Bachelor's degree.

• Specialization Profiles & Career Metrics:

  • Software Engineering:

    • Core Skills: Complex problem solving, critical thinking, programming logic.

    • Degree Credit Requirement: $120\text{ credits}$.

    • Average Annual Compensation: $\$1,078.40$

    • Job Openings Count: Approximately $128,000$ positions.

  • Hardware Engineering:

    • Core Skills: Troubleshooting, system evaluation, hardware synthesis, circuit design.

    • Degree Credit Requirement: $120\text{ credits}$.

    • Average Annual Compensation: $\$1,127.60$

    • Job Openings Count: Approximately $87,000$ positions.

• Research vs. Development Track Focus:

  • Research Focus: Centered on mathematically complex analysis, theory, and foundational innovation.

  • Development Focus: Centered on design via established methods, testing, evaluation, manufacturing, production, operations, service, maintenance, and distribution.

Career Readiness, IT Certifications, and Internship Strategies

• Role of IT Certifications:

  • Academic degrees alone are insufficient for modern technical employment; industry requires a combination of formal degrees and industry certifications.

  • Key Certifications: CompTIA A+, CompTIA Security+, CompTIA CySA+ (ISA+), and Cisco CCNA.

  • Financial Risk: Official certification voucher fees cost between $\$320$ and $\$350$ per attempt. Failing due to lack of technical knowledge or acronym unfamiliarity results in lost voucher fees.

  • Free Training Resources: CUNY Continuing Education boot camps and non-profit organizations (such as the Per Scholas program) offer free prep courses in Artificial Intelligence (AI) and Business Intelligence (BI).

• Career Support & Campus Resources:

  • Professional Development Center: Located in the NAM Building; provides resume reviews, cover letter drafting, and placement assistance for part-time, full-time, and internship roles.

  • Handshake Platform: Students must register using their official student email address to access dedicated job and internship postings.

  • Software Licensing: All technical software required for software engineering, computer engineering technology, or cybersecurity coursework must be downloaded using a valid student email address to receive free student licenses.

• Internship vs. Entry-Level Employment:

  • Entry-Level Job Barrier: Entry-level postings typically demand $2$ to $3$ years (or $4$ to $5$ years) of prior experience along with mastery of languages like C++, Java, and Python.

  • Internship Advantage: Internship programs understand that candidates are active students without experience. Internships build real-world experience, teamwork, and communication skills, which recruiters treat as verified job experience.

  • Key Internship Outlets: CUNY IT Internship Opportunities and the Brooklyn Navy Yard Internship Program. Students must inspect student email and Brightspace accounts daily to avoid missing critical deadlines.

Hardware Architecture, Computer Classification, and Microcontrollers

• Core Hardware Architecture:

  • Central Processing Unit (CPU): Executes instructions and performs mathematical/logical calculations.

  • Main Memory (RAM): Random Access Memory; volatile short-term primary memory.

  • Secondary Storage Devices: Hard drives, SSDs, and non-volatile long-term storage.

• Taxonomy of Computer Systems:

  • Classification by Type: Digital Computers, Analog Computers, and Hybrid Computers.

  • Classification by Purpose: Dedicated vs. General Purpose.

  • Classification by Size: Microcomputers, Mainframes, Supercomputers.

• Microcontrollers vs. General-Purpose Computers:

  • Central Processing Terminology:

    • The CPU of a microcontroller is formally designated as a microprocessor.

    • The CPU of a general-purpose computer is designated as a processor.

  • Clock Speed: Microcontrollers operate around $16\text{ MHz}$, whereas computer processors operate in the multi-gigahertz range.

  • Processing Power (MIPS - Million Instructions Per Second):

    • Low-End Microcontrollers (MCUs): Approximately $20\text{ MIPS}$.

    • High-End Microcontrollers (MCUs): Approximately $100\text{ MIPS}$.

    • Low-End Computer Processors: Approximately $500\text{ MIPS}$.

    • High-End Computer Processors: Approximately $5,000\text{ MIPS}$.

  • Embedded Microcontroller Applications: Adds computational intelligence to everyday items such as ATMs, automated car keys, cell phones, and embedded control modules.

BBC Micro:bit Architecture and Technical Specifications

• Course Hardware Requirement:

  • Required specifically for the Lab section of the course (not the lecture section).

  • Must be acquired via full kit links (such as Amazon or Electronic Express) to ensure all necessary peripheral hardware is included.

• Micro:bit Front View Components:

  • Programmable Buttons: $2$ tactile input switches (Button A and Button B).

  • Input/Output Rings: $3$ digital/analog input/output rings alongside power and ground connections.

  • LED Array: $25$ individual, independently programmable LEDs configured in a $5 \times 5$ grid display.

  • Power Connectors: Ground ring and power rings.

• Micro:bit Back View Components:

  • Motion & Orientation Sensors: Integrated Accelerometer and Magnetometer (Compass).

  • Edge Connector: $20\text{-pin}$ multi-bus edge connector.

  • Power & Connectivity Ports: Dedicated battery pack connector, micro-USB connector port, and on-board system sensors.

Operational Mechanics and Fundamental Computational Thinking

• Low-Level Operational Mechanics:

  • Machine Language: Operates entirely in binary code consisting of two values: $1$ (representing On) and $0$ (representing Off).

  • General Operation Sequence: Physical Input $\rightarrow$ Data Storage $\rightarrow$ Processing $\rightarrow$ Physical Output.

• Computational Thinking (CT):

  • Definition: The thought processes involved in formulating problems and expressing their solutions in ways that a computer can execute.

  • Core Goal: Expressing problems logically to solve them using computational tools.

• The 5 Pillars of Computational Thinking:

  1. Decomposition (Divide and Conquer):

     • Breaking down a complex problem into smaller, manageable sub-problems that can be analyzed and solved individually.

     • Sub-problem Recursion: If a sub-problem is still too complex, it can be decomposed further.

     • Example: Organizing a travel plan from New York to the Eiffel Tower in Paris. Decomposed into transport choices (NY to Paris flight, local Paris transit to Eiffel Tower) and ticketing requirements.

  2. Abstraction (Detail Removal):

     • Filtering out unnecessary information to focus exclusively on essential aspects.

     • Example: Standard street maps retain roads, landmarks, and rivers while omitting internal building structures. Metro maps abstract even further, showing only transit lines, stops, and major rivers.

  3. Pattern Recognition (Trend Spotting):

     • Identifying similarities, trends, and shared characteristics across historical instances to solve new problems efficiently.

     • Example: Analyzing opponent team strategies in sports to adopt tactics that succeeded in previous match-ups.

  4. Algorithm Design (Rule Creation):

     • Establishing clear, step-by-step instructions and explicit rules to execute a process or solve a problem.

     • Example: Decimal multiplication by $10$. To calculate:             $4.341 \times 10 = 43.41$             The defined algorithmic rule shifts the decimal point exactly one position to the right.

  5. Evaluation (Testing & Quality Assessment):

     • Critiquing and testing solutions against performance metrics: user suitability, ease of understanding, processing efficiency, and optimal resource consumption.

Algorithmic Execution, Flowcharts, Debugging, and Constructs

• Flowchart Representation:

  • Definition: Graphical representation of an algorithm utilizing standardized geometric symbols.

  • Pass/Fail Logic Example:

    • Start node $\rightarrow$ Read Grade node $\rightarrow$ Conditional Decision Box: Is Grade $\ge 60$?

    • If Yes: Directs to `Output