This document discusses algorithms and pseudocode. It defines an algorithm as a set of steps to solve a problem and notes that algorithms must be unambiguous and halt in finite time. The document outlines the steps to solve computational problems and lists characteristics of algorithms. It also defines pseudocode as a high-level description of an algorithm without programming syntax but allows estimating runtime. The difference between algorithms and pseudocode is explained, with algorithms being more formal and pseudocode being more descriptive. An example insertion sort algorithm and its pseudocode are provided.
Algorithms Lecture 1: Introduction to AlgorithmsMohamed Loey
Â
We will discuss the following: Algorithms, Time Complexity & Space Complexity, Algorithm vs Pseudo code, Some Algorithm Types, Programming Languages, Python, Anaconda.
HOW ARTIFICIAL INTELLIGENCE AND ITS SOFTWARES AND SMART ALGORITHMS WORK.pdfFaga1939
Â
This article aims to present how Artificial Intelligence, its software and its intelligent algorithms work, as well as the advantages and disadvantages of its use. Artificial intelligence (AI) is a computational technology developed with the aim of enabling machines to solve a series of problems, covering everything from the great complexity of government and industry management to the daily tasks of modern men and women. To do this, AI uses sophisticated learning technology, allowing the AI to learn from a large set of data and act on its own. Algorithms are the essence of any artificial intelligence system that are fed with as much data as possible, as references, so that they can learn better. It is important to note that unlike the algorithm, software is a type of system that allows the user to interact with the computer and gives instructions to the computer to perform specific tasks as well as control the functioning of the hardware and its operations. The advantages of using artificial intelligence include: 1) Reduction in human error; 2) Takes risks instead of human beings; 3) Availability of use (24 hours in 7 days); 4) Help with repetitive work; 5) Offers digital assistance; 6) Provides faster decisions; 7) Provides daily applications; 8) Promotes innovation. As a disadvantage, the use of artificial intelligence could cause machines to become so developed that humans will not be able to keep up with them and they will be able to continue on their own, redesigning themselves at an exponential rate, which could lead to invasion of people's privacy and even being turned into weapons and could lead to the extinction of the human race, in addition to promoting the advancement of unemployment, whether among manual workers or intellectual workers, because intelligent machines will also become workers.
Algorithms Lecture 1: Introduction to AlgorithmsMohamed Loey
Â
We will discuss the following: Algorithms, Time Complexity & Space Complexity, Algorithm vs Pseudo code, Some Algorithm Types, Programming Languages, Python, Anaconda.
HOW ARTIFICIAL INTELLIGENCE AND ITS SOFTWARES AND SMART ALGORITHMS WORK.pdfFaga1939
Â
This article aims to present how Artificial Intelligence, its software and its intelligent algorithms work, as well as the advantages and disadvantages of its use. Artificial intelligence (AI) is a computational technology developed with the aim of enabling machines to solve a series of problems, covering everything from the great complexity of government and industry management to the daily tasks of modern men and women. To do this, AI uses sophisticated learning technology, allowing the AI to learn from a large set of data and act on its own. Algorithms are the essence of any artificial intelligence system that are fed with as much data as possible, as references, so that they can learn better. It is important to note that unlike the algorithm, software is a type of system that allows the user to interact with the computer and gives instructions to the computer to perform specific tasks as well as control the functioning of the hardware and its operations. The advantages of using artificial intelligence include: 1) Reduction in human error; 2) Takes risks instead of human beings; 3) Availability of use (24 hours in 7 days); 4) Help with repetitive work; 5) Offers digital assistance; 6) Provides faster decisions; 7) Provides daily applications; 8) Promotes innovation. As a disadvantage, the use of artificial intelligence could cause machines to become so developed that humans will not be able to keep up with them and they will be able to continue on their own, redesigning themselves at an exponential rate, which could lead to invasion of people's privacy and even being turned into weapons and could lead to the extinction of the human race, in addition to promoting the advancement of unemployment, whether among manual workers or intellectual workers, because intelligent machines will also become workers.
Analysis and Design of Algorithms (ADA): An In-depth Exploration
Introduction:
The field of computer science is heavily reliant on algorithms to solve complex problems efficiently. The analysis and design of algorithms (ADA) is a fundamental area of study that focuses on understanding and creating efficient algorithms. This comprehensive overview will delve into the various aspects of ADA, including its importance, key concepts, techniques, and applications.
Importance of ADA:
Efficient algorithms play a critical role in various domains, including software development, data analysis, artificial intelligence, and optimization. ADA provides the tools and techniques necessary to design algorithms that are both correct and efficient. By analyzing the performance characteristics of algorithms, ADA enables computer scientists and engineers to develop solutions that save time, resources, and computational power.
Key Concepts in ADA:
Correctness: ADA emphasizes the importance of designing algorithms that produce correct outputs for all possible inputs. Techniques like mathematical proofs and induction are used to establish the correctness of algorithms.
Complexity Analysis: ADA seeks to analyze the efficiency of algorithms by examining their time and space complexity. Time complexity measures the amount of time required by an algorithm to execute, while space complexity measures the amount of memory consumed.
Asymptotic Notations: ADA employs asymptotic notations, such as Big O, Omega, and Theta, to express the growth rates of functions and classify the efficiency of algorithms. These notations allow for a concise comparison of algorithmic performance.
Algorithm Design Paradigms: ADA explores various design paradigms, including divide and conquer, dynamic programming, greedy algorithms, and backtracking. Each paradigm offers a systematic approach to solving problems efficiently.
Techniques in ADA:
Divide and Conquer: This technique involves breaking down a problem into smaller subproblems, solving them independently, and combining the solutions to obtain the final result. Well-known algorithms like Merge Sort and Quick Sort utilize the divide and conquer approach.
Dynamic Programming: Dynamic programming breaks down a complex problem into a series of overlapping subproblems and solves them in a bottom-up manner. This technique optimizes efficiency by storing and reusing intermediate results. The Fibonacci sequence calculation is a classic example of dynamic programming.
Greedy Algorithms: Greedy algorithms make locally optimal choices at each step, with the hope of achieving a global optimal solution. These algorithms are efficient but may not always yield the best overall solution. The Huffman coding algorithm for data compression is a widely used example of a greedy algorithm.
Backtracking: Backtracking involves searching for a solution to a problem by incrementally building a solution and undoing the choices that lead to dead-ends.
Analysis and Design of Algorithms (ADA): An In-depth Exploration
Introduction:
The field of computer science is heavily reliant on algorithms to solve complex problems efficiently. The analysis and design of algorithms (ADA) is a fundamental area of study that focuses on understanding and creating efficient algorithms. This comprehensive overview will delve into the various aspects of ADA, including its importance, key concepts, techniques, and applications.
Importance of ADA:
Efficient algorithms play a critical role in various domains, including software development, data analysis, artificial intelligence, and optimization. ADA provides the tools and techniques necessary to design algorithms that are both correct and efficient. By analyzing the performance characteristics of algorithms, ADA enables computer scientists and engineers to develop solutions that save time, resources, and computational power.
Key Concepts in ADA:
Correctness: ADA emphasizes the importance of designing algorithms that produce correct outputs for all possible inputs. Techniques like mathematical proofs and induction are used to establish the correctness of algorithms.
Complexity Analysis: ADA seeks to analyze the efficiency of algorithms by examining their time and space complexity. Time complexity measures the amount of time required by an algorithm to execute, while space complexity measures the amount of memory consumed.
Asymptotic Notations: ADA employs asymptotic notations, such as Big O, Omega, and Theta, to express the growth rates of functions and classify the efficiency of algorithms. These notations allow for a concise comparison of algorithmic performance.
Algorithm Design Paradigms: ADA explores various design paradigms, including divide and conquer, dynamic programming, greedy algorithms, and backtracking. Each paradigm offers a systematic approach to solving problems efficiently.
Techniques in ADA:
Divide and Conquer: This technique involves breaking down a problem into smaller subproblems, solving them independently, and combining the solutions to obtain the final result. Well-known algorithms like Merge Sort and Quick Sort utilize the divide and conquer approach.
Dynamic Programming: Dynamic programming breaks down a complex problem into a series of overlapping subproblems and solves them in a bottom-up manner. This technique optimizes efficiency by storing and reusing intermediate results. The Fibonacci sequence calculation is a classic example of dynamic programming.
Greedy Algorithms: Greedy algorithms make locally optimal choices at each step, with the hope of achieving a global optimal solution. These algorithms are efficient but may not always yield the best overall solution. The Huffman coding algorithm for data compression is a widely used example of a greedy algorithm.
Backtracking: Backtracking involves searching for a solution to a problem by incrementally building a solution and undoing the choices that lead to dead-ends.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Â
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
A Strategic Approach: GenAI in EducationPeter Windle
Â
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Â
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Â
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Delivering Micro-Credentials in Technical and Vocational Education and TrainingAG2 Design
Â
Explore how micro-credentials are transforming Technical and Vocational Education and Training (TVET) with this comprehensive slide deck. Discover what micro-credentials are, their importance in TVET, the advantages they offer, and the insights from industry experts. Additionally, learn about the top software applications available for creating and managing micro-credentials. This presentation also includes valuable resources and a discussion on the future of these specialised certifications.
For more detailed information on delivering micro-credentials in TVET, visit this https://tvettrainer.com/delivering-micro-credentials-in-tvet/
1. Artificial Intelligence
Sanjivani Rural Education Society’s
Sanjivani College of Engineering, Kopargaon-423603
(An Autonomous Institute Affiliated to Savitribai Phule Pune University, Pune)
NAAC ‘A’ Grade Accredited, ISO 9001:2015 Certified
Department of Information Technology
(NBA Accredited)
Mr. Y.S.Deshmukh
Assistant Professor
2. Design and Analysis of Algorithms
Design and Analysis of Algorithms – Unit 1 Part 1 Mr. Y.S.Deshmukh Department of Information Technology
Definition
Introduction
Algorithm Design
Problem Development Steps
Characteristics of Algorithms
Pseudocode
Difference between Algorithm and Pseudocode
3. Design and Analysis of Algorithms
Design and Analysis of Algorithms – Unit 1 Part 1 Mr. Y.S.Deshmukh Department of Information Technology
An Algorithm is a sequence of steps to solve a problem. Design
and Analysis of Algorithm is very important for designing
algorithm to solve different types of problems in the branch of
computer science and information technology.
Definition:-
4. Design and Analysis of Algorithms
Design and Analysis of Algorithms – Unit 1 Part 1 Mr. Y.S.Deshmukh Department of Information Technology
An algorithm is a set of steps of operations to solve a problem performing
calculation, data processing, and automated reasoning tasks. An algorithm
is an efficient method that can be expressed within finite amount of time
and space.
An algorithm is the best way to represent the solution of a particular
problem in a very simple and efficient way. If we have an algorithm for a
specific problem, then we can implement it in any programming
language, meaning that the algorithm is independent from any
programming languages.
Introduction:-
5. Design and Analysis of Algorithms
Design and Analysis of Algorithms – Unit 1 Part 1 Mr. Y.S.Deshmukh Department of Information Technology
The important aspects of algorithm design include creating an efficient
algorithm to solve a problem in an efficient way using minimum time and
space.
To solve a problem, different approaches can be followed. Some of them
can be efficient with respect to time consumption, whereas other
approaches may be memory efficient. However, one has to keep in mind
that both time consumption and memory usage cannot be optimized
simultaneously. If we require an algorithm to run in lesser time, we have
to invest in more memory and if we require an algorithm to run with
lesser memory, we need to have more time.
Algorithm Design:-
6. Design and Analysis of Algorithms
Design and Analysis of Algorithms – Unit 1 Part 1 Mr. Y.S.Deshmukh Department of Information Technology
The following steps are involved in solving computational problems.
1. Problem definition
2. Development of a model
3. Specification of an Algorithm
4. Designing an Algorithm
5. Checking the correctness of an Algorithm
6. Analysis of an Algorithm
7. Implementation of an Algorithm
8. Program testing
9. Documentation
Problem Development Steps:-
7. Design and Analysis of Algorithms
Design and Analysis of Algorithms – Unit 1 Part 1 Mr. Y.S.Deshmukh Department of Information Technology
The main characteristics of algorithms are as follows −
1. Algorithms must have a unique name
2. Algorithms should have explicitly defined set of inputs and outputs
3. Algorithms are well-ordered with unambiguous operations
4. Algorithms halt in a finite amount of time. Algorithms should not run
for infinity, i.e., an algorithm must end at some point
Characteristics of Algorithms:-
8. Design and Analysis of Algorithms
Design and Analysis of Algorithms – Unit 1 Part 1 Mr. Y.S.Deshmukh Department of Information Technology
Pseudocode gives a high-level description of an algorithm without the
ambiguity associated with plain text but also without the need to know
the syntax of a particular programming language.
The running time can be estimated in a more general manner by using
Pseudocode to represent the algorithm as a set of fundamental operations
which can then be counted.
Pseudocode:-
9. Design and Analysis of Algorithms
Design and Analysis of Algorithms – Unit 1 Part 1 Mr. Y.S.Deshmukh Department of Information Technology
An algorithm is a formal definition with some specific characteristics that
describes a process, which could be executed by a Turing-complete
computer machine to perform a specific task. Generally, the word
"algorithm" can be used to describe any high level task in computer
science.
On the other hand, pseudocode is an informal and (often rudimentary)
human readable description of an algorithm leaving many granular details
of it. Writing a pseudocode has no restriction of styles and its only
objective is to describe the high level steps of algorithm in a much
realistic manner in natural language.
Difference between Algorithm and Pseudocode:-
10. Design and Analysis of Algorithms
Design and Analysis of Algorithms – Unit 1 Part 1 Mr. Y.S.Deshmukh Department of Information Technology
Algorithm: Insertion-Sort
Input: A list L of integers of length n
Output: A sorted list L1 containing those integers present in L
Step 1: Keep a sorted list L1 which starts off empty
Step 2: Perform Step 3 for each element in the original list L
Step 3: Insert it into the correct position in the sorted list L1.
Step 4: Return the sorted list
Step 5: Stop
Algorithm for Insertion Sort:-
11. Design and Analysis of Algorithms
Design and Analysis of Algorithms – Unit 1 Part 1 Mr. Y.S.Deshmukh Department of Information Technology
for i <- 1 to length(A)
x <- A[i]
j <- i
while j > 0 and A[j-1] > x
A[j] <- A[j-1]
j <- j - 1
A[j] <- x
Pseudocode:-
12. Design and Analysis of Algorithms
Design and Analysis of Algorithms – Overview Mr. Y.S.Deshmukh Department of Information Technology
Thank You