Introduction to Computer Applications (MIS 103)

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Questions and Answers

Which methodological approach to problem-solving advocates for recursively breaking down a complex problem into smaller, more manageable sub-problems?

  • Iterative Aggregation and Simplification
  • Problem Decomposition (correct)
  • Work Breakdown Structure
  • Algorithmic Reductionism

In the context of ChatGPT's language generation, how does the temperature parameter influence the characteristics of the generated text?

  • It dictates the level of domain-specific jargon and technical terms included, adapting the text's complexity to a specific audience.
  • It strictly enforces grammatical correctness and adherence to formal language conventions, mitigating creative deviations.
  • It optimizes the length of the generated text by dynamically adjusting word sequence repetition, enhancing efficiency.
  • It regulates the balance between determinism and randomness by influencing the selection probability of subsequent words. (correct)

Which component of computational thinking involves discerning and abstracting key characteristics from multifaceted scenarios to formulate simplified or generalized representations?

  • Pattern Recognition
  • Abstraction (correct)
  • Algorithmic Optimization
  • Empirical Idealization

In the context of algorithmic design, 'correctness' exclusively pertains to generating outputs that are syntactically valid, even if semantically inaccurate or misleading.

<p>False (B)</p> Signup and view all the answers

Given a binary search algorithm operating on a sorted array of $n$ elements, what is the maximum number of comparisons required in the worst-case scenario, expressed in Big O notation?

<p>$O(log n)$</p> Signup and view all the answers

The principle of adapting a solution to accommodate more general cases, enhancing its reusability across diverse but related problems, is known as ______.

<p>generalization</p> Signup and view all the answers

Match the following tools to their respective applications in visual thinking.

<p>Control Flow Diagrams = Illustrate the execution flow in computer programs or algorithms. Mind Maps = Organize and brainstorm ideas around a central concept. Process Flow Diagrams = Visualize the sequence of steps in business processes. Swim Lane Diagrams = Delineate responsibilities and interactions among different actors in a process.</p> Signup and view all the answers

Considering a clothing retail store with a year's worth of sales data, what analytical emphasis would characterize the application of Pattern Recognition within the realm of Computational Thinking?

<p>Identify sales spikes or dips coinciding with specific seasons, holidays, or weekday versus weekend differences. (C)</p> Signup and view all the answers

Which of the following options regarding ChatGPT aligns best with the mechanism guiding its language generation capabilities?

<p>ChatGPT iteratively samples from a probability distribution over a vocabulary conditioned on prior text. (A)</p> Signup and view all the answers

According to Denning (2009), "algorithmic thinking," as understood in the 1950s and 1960s, explicitly incorporates the use of varying levels of abstraction and mathematical formalisms to develop scalable solutions.

<p>False (B)</p> Signup and view all the answers

In visual thinking, how do swim lane diagrams enhance process analysis, distinct from basic process flow diagrams?

<p>Swim lane diagrams help analyze a process by showing which actor is responsible for each step.</p> Signup and view all the answers

In algorithmic analysis, the characteristic of ______ refers to capacity of an algorithm to reliably manage the execution, data integrity, and result precision in the face of non-nominal data or operational abnormalities.

<p>robustness</p> Signup and view all the answers

Match the definitions with the correct terms:

<p>Ability to identify and understand similarities and relationships within data. = Pattern Recognition Procedure for solving a problem. = Algorithm Design Method for taking a problem and breaking it into smaller parts. = Problem Decomposition Adapting formulated solutions or algorithms into different problem states. = Generalization</p> Signup and view all the answers

Regarding the principles and procedures applicable to establishing an effective search algorithm specifically designed for categorically unstructured, capaciously scaled databases:

<p>Execute a parallelized nearest-neighbor heuristic predicated on locality-sensitive hashing to facilitate scalable retrieval. (A)</p> Signup and view all the answers

Within the framework of a commercial business intelligence initiative, envisage a scenario characterized by the need to furnish an exhaustive delineation pertaining to the successive stages inherent to client onboarding.

<p>A process flow diagram (D)</p> Signup and view all the answers

According to initial indications, GPT-2's performance—in stark contrast to its subsequent and superior GPT-3 variant—exhibited relative parity in automated deductive competency when juxtaposed against its counterparts predicated on analogous architectural designs but trained employing datasets exhibiting diminished cardinality and/or curtailed entropic diversity.

<p>False (B)</p> Signup and view all the answers

Construct a minimal pseudo-code excerpt that elucidates a binary search algorithm’s central logic, assuming variables low, high, list, and target.

<p><code>while low &lt;= high: mid = (low + high) // 2 if list[mid] == target: return mid elif list[mid] &lt; target: low = mid + 1 else: high = mid - 1 return None</code></p> Signup and view all the answers

When crafting a Haiku, the integration of a ________, which alludes to seasonal context, serves as a compositional fulcrum, grounding the verses in a time-specific milieu.

<p>kigo</p> Signup and view all the answers

Match the AI concepts given.

<p>Supervised Learning = Learning from task-labelled, complete datasets Unsupervised Learning = Deriving conclusions while labeling datasets. Transfer Learning = Applying skills learned from one place to the other Reinforcement Learning = Trial by error method</p> Signup and view all the answers

Which one of the following properties defines a robust algorithm in the context of computational thinking?

<p>Ability to deliver consistent results, even when the provided inputs are non-standard or include errors. (D)</p> Signup and view all the answers

Within the context of designing an AI-driven predictive maintenance system for industrial machinery, which paradigm from the toolbox of visual thinking could most succinctly elucidate symbiotic human-machine interactions?

<p>Swim Lane Diagrams (C)</p> Signup and view all the answers

According to descriptions given, if Haiku only utilizes three lines, then by extension it needs to rhyme?

<p>False (B)</p> Signup and view all the answers

Elaborate the utility of a well-structured Work Breakdown Structure (WBS) in orchestrating a project.

<p>A work breakdown structure helps decompose projects to better allocate time and make task dependencies.</p> Signup and view all the answers

Within the paradigm of ChatGPT functionality, the '______ parameter' fine-tunes the stochasticity governing lexical selection such that higher magnitudes foster generation of off-trajectory or tangential textual content.

<p>temperature</p> Signup and view all the answers

Match the following visual thinking tools to their typical use.

<p>Mind Maps = Brainstorming sessions to explore related ideas. Control Flow Diagrams = Graphically representing the steps in a computer program. Process Flow Diagrams = Document the stages of business operations. Swim Lane Diagrams = Illustrating roles in a processes.</p> Signup and view all the answers

What constitutes the most critical advantage of using binary search over linear search when operating on capacious, pre-ordered datasets?

<p>Logarithmic Time Efficiency (B)</p> Signup and view all the answers

What is the correct interpretation of abstraction within computation thinking?

<p>Understanding necessary details while ignoring unimportant variables. (A)</p> Signup and view all the answers

A Kireji in Haiku must always come at the end of the lines.

<p>False (B)</p> Signup and view all the answers

How do control flow charts show computer program algorithms efficiently?

<p>Control flow charts graphically point the program and algorithm efficiently.</p> Signup and view all the answers

By parsing and analyzing sales data from last year, ______ ensures there are winter jacket sales or summer swimsuits.

<p>seasonality</p> Signup and view all the answers

Match:

<p>A Haiku must have three lines. = Haiku rules Abstraction = Focuses on necessary details while ignoring the unnecessary ones Algorithm = Step-by-step procedure for solving a problem Efficiency = Measure taken to solve the problem to save time and space</p> Signup and view all the answers

In a well-defined algorithm, which characteristic ensures that the result always corresponds to its correct output for every input?

<p>Correctness (A)</p> Signup and view all the answers

What is the intent of a swim lane diagram?

<p>To visualize how different roles interact in a business. (D)</p> Signup and view all the answers

Visual thinking is the utilization of verbal representation to organize ideas.

<p>False (B)</p> Signup and view all the answers

In computer science and computational thinking, what is the method that focuses on efficient computer usage?

<p>Efficient and effective computer use</p> Signup and view all the answers

To formulate complex problems ______ is used for simplification.

<p>abstraction</p> Signup and view all the answers

Match each statement to the correct principle of algorithm design:

<p>Algorithm should handle unexpected inputs and errors. = Robustness Algorithm should solve the problem within an efficient allowance of space and time = Efficiency Algorithm should be direct and easy to interpret = Simplicity Algorithm should produce the correct output for possible inputs. = Correctness</p> Signup and view all the answers

Flashcards

Computational Thinking

Efficient and effective computer use

Abstraction

Focusing on essential details and ignoring unnecessary ones

Problem Decomposition

Breaking down a problem into smaller, manageable parts

Algorithm

Step-by-step procedure for solving a problem

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Pattern Recognition

Ability to identify patterns and relationships in data

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Generalization

Adapting solutions to different problem states, different variables

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Visual Thinking

A thought process that organizes ideas visually using graphical representation

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Mind Mapping

A visual thought process to identify a central idea and related brainstorming

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Control Flow Diagram

Graphical representation for the flow of execution of a computer program

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Process Flow Diagram

A flowchart illustrating a business process's sequence of steps

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Swim-Lane Diagram

A diagram delineating who does what in a process

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Work Breakdown Structure

Tool for breaking down complex projects.

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Study Notes

  • The course is called Introduction to Computer Applications (MIS 103)
  • The course instructor is Usman Ali, a Lecturer
  • Usman Ali is pursuing a PhD in Computer Science, specializing in Machine Learning, at IBA Karachi
  • Course timings are Mondays and Wednesdays at either 8:30 AM, 10:00 AM, or 2:30 PM
  • Classes are held in the Finance Lab, MCL3

Course Description

  • The course equips students with structured problem-solving, computational thinking, and data analysis skills in a business context
  • Designed for students without a computer science background
  • Aims to enable effective use of technology and information resources for data analysis

Program Learning Goals

  • Technology & Information Literacy (PLC5) focuses on the ability to leverage technology and information resources for data analysis and communication in a business context

Course Learning Outcomes (CLOs) :

  • CLO-1: Structured problem-solving using frameworks and tools
  • CLO-2: Essential programming fundamentals from a problem-solving and data analysis perspective
  • CLO-3: Data analysis in a business problem context

Teaching & Learning Methodology

  • Course includes pre-class reading, active class participation, and regular post-lecture follow-up
  • Lecture presentations and related resources are uploaded on the Learning Management System (LMS)
  • In-class lab assignments are graded to provide hands-on experience with tools and techniques
  • Unannounced quizzes cover theoretical and practical aspects

Weekly Course Content Overview:

  • Week 1: Computational Thinking, including Structured Problem Solving, Abstraction, and Algorithm Design
  • Week 2: Introduction to Python, Setup & Installation, Data Types
  • Week 3: Control Structures, including Python Operators, Conditional Statements, and Loops
  • Weeks 4 & 5: Container Data Types, including Lists, Sets, Tuples, and Dictionaries
  • Weeks 5 & 6: Functions, including Variable Scope, Arguments and Parameters, and Lambda Functions
  • Week 7: Files and Exception Handling, covering file types, text file manipulation, and error handling mechanisms

Course topics:

  • Working with Pandas, including DataFrames, Series, and Data Aggregation
  • Handling Data Quality Problems, including Missing Values and Data Type Issues
  • Working with NumPy, including Array creation and arithmetic operations
  • Statistical Analysis, including Normal Distribution and Correlation Analysis
  • EDA using Data Visualization, including Matplotlib, Seaborn, and Plotly
  • Key dates in 2025 include:
    • Midterm Exam: March 17-22 (Mon- Sat)
    • Mid-semester Break: March 24-29 (Mon- Sat)
    • Classes End: May 19 (Monday)
    • Final Exam: May 21 to June 03 (Wed - Tue)
    • Result Submission Deadline: June 18

Grading and Assessment

  • Absolute grading based on IBA's grading scale
  • Class participation is graded on punctuality, discipline, and overall interactivity
  • Quizzes are hands-on, Hacker Tank-style, with MCQs based on Concepts
  • Lab assignments relate to Python and data analysis
  • Home assignments are based on end-of-chapter questions
  • A final group project based on a chosen dataset and business problem
  • There will be Midterm will be worth 20% and the Final Exam 30%

Course Guidelines:

  • Attendance is mandatory, with a maximum of 6 absences
  • Students are expected to keep up with the material and understand lectures
  • Unethical behavior will be strictly penalized
  • Late submissions receive a 10% deduction on LMS, and no submissions are accepted after the deadline
  • No make-up for any quiz, lab assignment, home assignment and project

Computational Thinking

  • Computational Thinking involves efficient and effective computer use.
  • Pre-requisites include understanding how computers work and making human-computer interaction efficient

Definitions in Literature:

  • Computational thinking involves formulating problems and representing solutions for information-processing agents
  • It's a thought process used to formulate problems and express solutions for computer application
  • It relates to abstraction of problems and creation of automatable solutions
  • Furber describes it as recognizing computation aspects in the world and using computer science techniques

What is Common in Computational Thinking

  • Structured problem solving
  • Problem understanding & formulation
  • Designing solutions computers can process
  • Input conversion to output
  • Considering levels of abstraction
  • Using mathematics

Components of Computational Thinking

  • Skills needed to convert complex, real-world problems into a form a computer can tackle
  • Include abstraction, algorithms, automation, decomposition, parallelization, and generalization

Abstraction

  • Focusing on necessary details while ignoring unnecessary ones
  • Examples:
  • Drawing five balls and five stars, separated by a decision boundary
  • Sending an email by pressing the send button.

Problem Decomposition

  • A method involves breaking a problem into smaller, understandable parts (also known as "Divide and Conquer").

Algorithm Design

  • An algorithm is a step-by-step procedure for solving problems effectively
  • Guidelines for algorithm design include: correctness, efficiency, generality, simplicity, and robustness

Algorithm Design example

  • Calculating the net pay from a gross pay
  • Example Algorithms - Merge sort
  • Linear and Binary Search
  • Procedures include reading the search element, comparing it with each element, and displaying if found
  • The Array should be sorted before searching

Pattern Recognition

  • Identifying and understanding similarities and relationships within data or concepts.
  • Involves looking for repeating sequences or trends, analyzing common features, and comparing different parts

Pattern Recognition examples:

  • Identifying seasonal trends in sales data
  • Detecting fraudulent claims in insurance data

Generalization

  • Adapting formulated solutions or algorithms into different problem states, even if the variables involved are different

Visual Thinking tools

  • Mind maps
  • Process Flow Diagrams
  • Flow Charts
  • Visual Programming
  • Swim Lanes
  • State Diagrams
  • Transition Tables
  • UML Diagrams

Mind Mapping

  • A visual thought process that assists you to identify a central idea, brainstorm related ideas
  • Elements of a mind map: central image/concept, branches, sub-branches, and symbols

Control Flow Diagrams (CFD)

  • A graphical representation that shows the complete flow of execution of a computer program or algorithm
  • Contains nodes, arrows, decision nodes, and terminal nodes

Process Flow Diagrams (PFD)

  • A flowchart that illustrates the sequence of steps needed to complete a business process
  • Uses standardized symbols to describe and depict the flow between each step

Swim Lane Diagrams

  • Delineates who does what in a process.
  • Provides clarity and accountability

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