USE OF SPLIT() FUNCTION TO READ WORDS AND USING IF CONDITION CHECK THOSE WORDS ARE UPPER,LOWER,VOWELS ETC.
DOWNLOAD YOUTUBE VIDEO:
https://youtu.be/ByKLhofw7jA
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Presented at the European Bioinformatics Institute (17th March 2017)
We often talk about good code — that we would like to write it, that there isn't enough of it, that it should not be considered an optional attribute of a codebase. We often talk about it but, when it comes to being precise, we don't always agree what constitutes good code, nor do we necessarily share a common view on its value.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Presented at the European Bioinformatics Institute (17th March 2017)
We often talk about good code — that we would like to write it, that there isn't enough of it, that it should not be considered an optional attribute of a codebase. We often talk about it but, when it comes to being precise, we don't always agree what constitutes good code, nor do we necessarily share a common view on its value.
Declare Your Language: Syntactic (Editor) ServicesEelco Visser
Lecture 3 on compiler construction course on definition of lexical syntax and syntactic services that can be derived from syntax definitions such as formatting and syntactic completion
For fun: An algorithm and Python Code for creating word chains between words of the same length. Words are linked on the chain if they differ by only one letter. All words must be English words (e.g. contained in Unix words file with possible additions of missing words). Example: wife -> life -> live -> love
These are the slides of the second part of this multi-part series, from Learn Python Den Haag meetup group. It covers List comprehensions, Dictionary comprehensions and functions.
Dok Talks #115 - What More Can I Learn From My OpenTelemetry Traces?DoKC
https://go.dok.community/slack
https://dok.community/
ABSTRACT OF THE TALK
Of the three observability data types supported by OpenTelemetry (metrics, logs, and traces) the latter is the one with most potential. Tracing gives users insights into how requests are processed by microservices in a modern, cloud-native architecture.
Jaeger and Grafana can visualize a single trace, showing how an individual request traversed your entire system. This helps for distributed debugging and analysis, but using traces only this way is limiting.
What if you stored tracing data in a SQL database? You could ask global questions about your system. You could find slow communication paths, where the error rate spiked since the last deployment, or where the request rate suddenly dropped. Thus, tracing can be used proactively to help you spot issues before your customers do.
This talk will show you how to do all the above by ingesting OpenTelemetry traces into a PostgreSQL/TimescaleDB database, and building custom dashboards using SQL to make the most out of your tracing data.
BIO
John Pruitt is a software engineer at Timescale. His work focuses on database/SQL development for the Promscale open-source observability tool, and currently on adding support for OpenTelemetry tracing. Prior to joining Timescale, John grew the DBA team at Shipt. Most of the balance of his career was spent building custom time-series applications in the energy industry and leading data warehousing efforts at regional banks.
KEY TAKE-AWAYS FROM THE TALK
- What is distributed tracing
- Why viewing individual traces is of limited value
- How SQL can be used to analyze and visualize traces
- What insights can be unlocked using SQL against traces
Ejercicios de estilo en la programaciónSoftware Guru
El escritor francés Raymond Queneau escribió a mediados del siglo XX un libro llamado "Ejercicios de Estilo" donde mostraba una misma historia corta, redactada de 99 formas distintas.
En esta plática realizaremos el mismo ejercicio con un programa de software. Abarcaremos distintos estilos y paradigmas: programación monolítica, orientada a objetos, relacional, orientada a aspectos, monadas, map-reduce, y muchos otros, a través de los cuales podremos apreciar la riqueza del pensamiento humano aplicado a la computación.
Esto va mucho más allá de un ejercicio académico; el diseño de sistemas de gran escala se alimenta de esta variedad de estilos. También platicaremos sobre los peligros de quedar atrapado bajo un conjunto reducido de estilos a lo largo de tu carrera, y la necesidad de verdaderamente entender distintos estilos al diseñar arquitecturas de sistemas de software.
Semblanza del conferencista:
Crista Lopez es profesora en la Facultad de Ciencias Computacionales de la Universidad de California en Irvine. Su investigación se enfoca en prácticas de ingeniería de software para sistemas de gran escala. Previamente, fue miembro fundador del equipo en Xerox PARC creador del paradigma de programación orientado a aspectos (AOP). Crista es una de las desarrolladoras principales de OpenSimulator, una plataforma open source para crear mundos virtuales 3D. También es fundadora de Encitra, empresa especializada en la utilización de la realidad virtual para proyectos de desarrollo urbano sustentable. @cristalopes
Function Applicative for Great Good of Palindrome Checker Function - Polyglot...Philip Schwarz
Embark on an informative and fun journey through everything you need to know to understand how the Applicative instance for functions makes for a terse palindrome checker function definition in point-free style.
CSE 220 Assignment 3 Hints and Tips Some hints for approa.docxfaithxdunce63732
CSE 220 Assignment 3 Hints and Tips
Some hints for approaching this assignment is as follows:
Approaching the assignment :
General Overview
It would be a good thing if before you start your assignment you try to decompose the problem
you are trying to solve into small segments. Each segment can be then written and tested for
any bugs or errors. Doing so will help you learn the true nature of functions and how effective
they can be.
The assignment requires that you read a string from either the stdin or a file and then count the
frequency of words in it and display it to stdout or to a file. We can look at this in the following
way :
1) Read an input from one of two sources
a. stdin
b. an input file
2) Find the frequency of words from input string
3) Write the words and their frequency to one of two ouputs
a. Stdout
b. An outputifle
One way of solving the problem
One way of approaching this code would be to create a structure which will hold a word and its
frequency and then create an array of that structure to accommodate all the unique words in
the input. So you would create a structure as follows:
struct wordStorage
{
char word[50];
int count;
};
Then when you want to create an array of that structure you would write it out as :
struct wordStorage arr[size];
So we created an array to of size number of elements of the structure wordStorage created
above.
This array can then be used to keep track of all the unique words you come across in the input
string and their frequencies. You can create arrays of this structure after you have defined the
structure itself.
You could then use the following prototypes in your code:
1. void decomposeToArray(char *para,char wordarr[1000][50])
This function takes in a string para and stores all the words in that string. You can
modify it to return the array of words containing all the words using –
char** decomposeToArray(char *para,char wordarr[1000][50]);
2. void frequencyOfWords(struct wordStorage *wordarr,char wordList[1000][50])
This function takes in a structure array in which element contains a word and its
frequency and the array of words that you created using decomposeToArray(args).
Instead of using a void function you can modify it so that it stores the words and
their frequency as an array of the given structure and then returns the structure
array. The prototype then becomes –
struct wordStorage* frequencyOfWords(wordList[1000][50])
3. void readFromFile(char *filename,char sentence[1000])
This function takes in the name of a file and a string to store all the contents of the
file. You can use pass by reference to keep track of the string that is storing the
string OR you could modify the function to read the name of a file and return a
string using:
char* readFromFile(char *filename)
4. void writeToFile(char *filename,struct wordStorage *wordarr);
This function prints the contents of the struct.
INFORMATIVE ESSAYThe purpose of the Informative Essay assignme.docxcarliotwaycave
INFORMATIVE ESSAY
The purpose of the Informative Essay assignment is to choose a job or task that you know how to do and then write a minimum of 2 full pages, maximum of 3 full pages, Informative Essay teaching the reader how to do that job or task. You will follow the organization techniques explained in Unit 6.
Here are the details:
1. Read the Lecture Notes in Unit 6. You may also find the information in Chapter 10.5 in our text on Process Analysis helpful. The lecture notes will really be the most important to read in writing this assignment. However, here is a link to that chapter that you may look at in addition to the lecture notes:
https://open.lib.umn.edu/writingforsuccess/chapter/10-5-process-analysis/ (Links to an external site.)
2. Choose your topic, that is, the job or task you want to teach. As the notes explain, this should be a job or task that you already know how to do, and it should be something you can do well. At this point, think about your audience (reader). Will your reader need any knowledge or experience to do this job or task, or will you write these instructions for a general reader where no experience is required to perform the job?
3. Plan your outline to organize this essay. Unit 6 notes offer advice on this organization process. Be sure to include an introductory paragraph that has the four main points presented in the lecture notes.
4. Write the essay. It will need to be at least 2 FULL pages long, maximum of 3 full pages long. You will use the MLA formatting that you used in previous essays from Units 3, 4, and 5.
5. Be sure to include a title for your essay.
6. After writing the essay, be sure to take time to read it several times for revision and editing. It would be helpful to have at least one other person proofread it as well before submitting the assignment.
Quiz2
# comments start with #
# to quit q()
# two steps to install any library
#install.packages("rattle")
#library(rattle)
setwd("D:/AJITH/CUMBERLANDS/Ph.D/SEMESTER 3/Data Science & Big Data Analy (ITS-836-51)/RStudio/Week2")
getwd()
x <- 3 # x is a vector of length 1
print(x)
v1 <- c(2,4,6,8,10)
print(v1)
print(v1[3])
v <- c(1:10) #creates a vector of 10 elements numbered 1 through 10. More complicated data
print(v)
print(v[6])
# Import test data
test<-read.csv("CVEs.csv")
test1<-read.csv("CVEs.csv", sep=",")
test2<-read.table("CVEs.csv", sep=",")
write.csv(test2, file="out.csv")
# Write CSV in R
write.table(test1, file = "out1.csv",row.names=TRUE, na="",col.names=TRUE, sep=",")
head(test)
tail(test)
summary(test)
head <- head(test)
tail <- tail(test)
cor(test$X, test$index)
sd(test$index)
var(test$index)
plot(test$index)
hist(test$index)
str(test$index)
quit()
Quiz3
setwd("C:/Users/ialsmadi/Desktop/University_of_Cumberlands/Lectures/Week2/RScripts")
getwd()
# Import test data
data<-read.csv("yearly_sales.csv")
#A 5-number summary is a set of 5 descriptive statistics for summarizing a continuous univariate data set.
#It consists o ...
Declare Your Language: Syntactic (Editor) ServicesEelco Visser
Lecture 3 on compiler construction course on definition of lexical syntax and syntactic services that can be derived from syntax definitions such as formatting and syntactic completion
For fun: An algorithm and Python Code for creating word chains between words of the same length. Words are linked on the chain if they differ by only one letter. All words must be English words (e.g. contained in Unix words file with possible additions of missing words). Example: wife -> life -> live -> love
These are the slides of the second part of this multi-part series, from Learn Python Den Haag meetup group. It covers List comprehensions, Dictionary comprehensions and functions.
Dok Talks #115 - What More Can I Learn From My OpenTelemetry Traces?DoKC
https://go.dok.community/slack
https://dok.community/
ABSTRACT OF THE TALK
Of the three observability data types supported by OpenTelemetry (metrics, logs, and traces) the latter is the one with most potential. Tracing gives users insights into how requests are processed by microservices in a modern, cloud-native architecture.
Jaeger and Grafana can visualize a single trace, showing how an individual request traversed your entire system. This helps for distributed debugging and analysis, but using traces only this way is limiting.
What if you stored tracing data in a SQL database? You could ask global questions about your system. You could find slow communication paths, where the error rate spiked since the last deployment, or where the request rate suddenly dropped. Thus, tracing can be used proactively to help you spot issues before your customers do.
This talk will show you how to do all the above by ingesting OpenTelemetry traces into a PostgreSQL/TimescaleDB database, and building custom dashboards using SQL to make the most out of your tracing data.
BIO
John Pruitt is a software engineer at Timescale. His work focuses on database/SQL development for the Promscale open-source observability tool, and currently on adding support for OpenTelemetry tracing. Prior to joining Timescale, John grew the DBA team at Shipt. Most of the balance of his career was spent building custom time-series applications in the energy industry and leading data warehousing efforts at regional banks.
KEY TAKE-AWAYS FROM THE TALK
- What is distributed tracing
- Why viewing individual traces is of limited value
- How SQL can be used to analyze and visualize traces
- What insights can be unlocked using SQL against traces
Ejercicios de estilo en la programaciónSoftware Guru
El escritor francés Raymond Queneau escribió a mediados del siglo XX un libro llamado "Ejercicios de Estilo" donde mostraba una misma historia corta, redactada de 99 formas distintas.
En esta plática realizaremos el mismo ejercicio con un programa de software. Abarcaremos distintos estilos y paradigmas: programación monolítica, orientada a objetos, relacional, orientada a aspectos, monadas, map-reduce, y muchos otros, a través de los cuales podremos apreciar la riqueza del pensamiento humano aplicado a la computación.
Esto va mucho más allá de un ejercicio académico; el diseño de sistemas de gran escala se alimenta de esta variedad de estilos. También platicaremos sobre los peligros de quedar atrapado bajo un conjunto reducido de estilos a lo largo de tu carrera, y la necesidad de verdaderamente entender distintos estilos al diseñar arquitecturas de sistemas de software.
Semblanza del conferencista:
Crista Lopez es profesora en la Facultad de Ciencias Computacionales de la Universidad de California en Irvine. Su investigación se enfoca en prácticas de ingeniería de software para sistemas de gran escala. Previamente, fue miembro fundador del equipo en Xerox PARC creador del paradigma de programación orientado a aspectos (AOP). Crista es una de las desarrolladoras principales de OpenSimulator, una plataforma open source para crear mundos virtuales 3D. También es fundadora de Encitra, empresa especializada en la utilización de la realidad virtual para proyectos de desarrollo urbano sustentable. @cristalopes
Function Applicative for Great Good of Palindrome Checker Function - Polyglot...Philip Schwarz
Embark on an informative and fun journey through everything you need to know to understand how the Applicative instance for functions makes for a terse palindrome checker function definition in point-free style.
CSE 220 Assignment 3 Hints and Tips Some hints for approa.docxfaithxdunce63732
CSE 220 Assignment 3 Hints and Tips
Some hints for approaching this assignment is as follows:
Approaching the assignment :
General Overview
It would be a good thing if before you start your assignment you try to decompose the problem
you are trying to solve into small segments. Each segment can be then written and tested for
any bugs or errors. Doing so will help you learn the true nature of functions and how effective
they can be.
The assignment requires that you read a string from either the stdin or a file and then count the
frequency of words in it and display it to stdout or to a file. We can look at this in the following
way :
1) Read an input from one of two sources
a. stdin
b. an input file
2) Find the frequency of words from input string
3) Write the words and their frequency to one of two ouputs
a. Stdout
b. An outputifle
One way of solving the problem
One way of approaching this code would be to create a structure which will hold a word and its
frequency and then create an array of that structure to accommodate all the unique words in
the input. So you would create a structure as follows:
struct wordStorage
{
char word[50];
int count;
};
Then when you want to create an array of that structure you would write it out as :
struct wordStorage arr[size];
So we created an array to of size number of elements of the structure wordStorage created
above.
This array can then be used to keep track of all the unique words you come across in the input
string and their frequencies. You can create arrays of this structure after you have defined the
structure itself.
You could then use the following prototypes in your code:
1. void decomposeToArray(char *para,char wordarr[1000][50])
This function takes in a string para and stores all the words in that string. You can
modify it to return the array of words containing all the words using –
char** decomposeToArray(char *para,char wordarr[1000][50]);
2. void frequencyOfWords(struct wordStorage *wordarr,char wordList[1000][50])
This function takes in a structure array in which element contains a word and its
frequency and the array of words that you created using decomposeToArray(args).
Instead of using a void function you can modify it so that it stores the words and
their frequency as an array of the given structure and then returns the structure
array. The prototype then becomes –
struct wordStorage* frequencyOfWords(wordList[1000][50])
3. void readFromFile(char *filename,char sentence[1000])
This function takes in the name of a file and a string to store all the contents of the
file. You can use pass by reference to keep track of the string that is storing the
string OR you could modify the function to read the name of a file and return a
string using:
char* readFromFile(char *filename)
4. void writeToFile(char *filename,struct wordStorage *wordarr);
This function prints the contents of the struct.
INFORMATIVE ESSAYThe purpose of the Informative Essay assignme.docxcarliotwaycave
INFORMATIVE ESSAY
The purpose of the Informative Essay assignment is to choose a job or task that you know how to do and then write a minimum of 2 full pages, maximum of 3 full pages, Informative Essay teaching the reader how to do that job or task. You will follow the organization techniques explained in Unit 6.
Here are the details:
1. Read the Lecture Notes in Unit 6. You may also find the information in Chapter 10.5 in our text on Process Analysis helpful. The lecture notes will really be the most important to read in writing this assignment. However, here is a link to that chapter that you may look at in addition to the lecture notes:
https://open.lib.umn.edu/writingforsuccess/chapter/10-5-process-analysis/ (Links to an external site.)
2. Choose your topic, that is, the job or task you want to teach. As the notes explain, this should be a job or task that you already know how to do, and it should be something you can do well. At this point, think about your audience (reader). Will your reader need any knowledge or experience to do this job or task, or will you write these instructions for a general reader where no experience is required to perform the job?
3. Plan your outline to organize this essay. Unit 6 notes offer advice on this organization process. Be sure to include an introductory paragraph that has the four main points presented in the lecture notes.
4. Write the essay. It will need to be at least 2 FULL pages long, maximum of 3 full pages long. You will use the MLA formatting that you used in previous essays from Units 3, 4, and 5.
5. Be sure to include a title for your essay.
6. After writing the essay, be sure to take time to read it several times for revision and editing. It would be helpful to have at least one other person proofread it as well before submitting the assignment.
Quiz2
# comments start with #
# to quit q()
# two steps to install any library
#install.packages("rattle")
#library(rattle)
setwd("D:/AJITH/CUMBERLANDS/Ph.D/SEMESTER 3/Data Science & Big Data Analy (ITS-836-51)/RStudio/Week2")
getwd()
x <- 3 # x is a vector of length 1
print(x)
v1 <- c(2,4,6,8,10)
print(v1)
print(v1[3])
v <- c(1:10) #creates a vector of 10 elements numbered 1 through 10. More complicated data
print(v)
print(v[6])
# Import test data
test<-read.csv("CVEs.csv")
test1<-read.csv("CVEs.csv", sep=",")
test2<-read.table("CVEs.csv", sep=",")
write.csv(test2, file="out.csv")
# Write CSV in R
write.table(test1, file = "out1.csv",row.names=TRUE, na="",col.names=TRUE, sep=",")
head(test)
tail(test)
summary(test)
head <- head(test)
tail <- tail(test)
cor(test$X, test$index)
sd(test$index)
var(test$index)
plot(test$index)
hist(test$index)
str(test$index)
quit()
Quiz3
setwd("C:/Users/ialsmadi/Desktop/University_of_Cumberlands/Lectures/Week2/RScripts")
getwd()
# Import test data
data<-read.csv("yearly_sales.csv")
#A 5-number summary is a set of 5 descriptive statistics for summarizing a continuous univariate data set.
#It consists o ...
Using High Dimensional Representation of Words (CBOW) to Find Domain Based Co...HPCC Systems
Text cleaning is becoming an essential step in text classification. Stop word removal is a crucial space-saving technique in text cleaning which saves huge amounts of space in text indexing. There are many domain-based common words which differ from one domain to another and have no value within a particular domain. Eliminating these words will reduce the size of the corpus and enhance the performance of text mining. This talk will discuss how the text vectors bundle, (CBOW), in HPCC Systems was used to find the domain based common words, and the methodology applied to enhance the performance of classification methods.
Perl is a very feature-rich language, which clearly cannot be discussed in full detail here. Instead, our
goals here are to (a) enable the reader to quickly become proficient at writing simple Perl programs and (b)
prepare the reader to consult full Perl books (or Perl tutorials on the Web) for further details of whatever
Perl constructs he/she needs for a particular application.
Our approach here is different from that of most Perl books, or even most Perl Web tutorials. The usual
approach is to painfully go over all details from the beginning. For example, the usual approach would be
to state all possible forms that a Perl literal can take on.
We avoid this here. Again, the aim is to enable the reader to quickly acquire a Perl foundation. He/she should
then be able to delve directly into some special topic, with little or not further learning of foundations.
Cosmetics Shop Management System is a complete solution for managing a Shop, in other words, an enhanced tool that assists in organizing the day-to-day activities of a Shop. There is the need of an application for efficient management and handling customer orders. This Cosmetics Shop Management System keeps every record Shop and reducing paperwork
The Computer Shop System is designed & developed for a computer shop to manage their records of selling and purchasing of the computer parts from the dealers and sell them to the customers. This system makes the work of the computer shopkeepers easy as it keeps all the records of the computer product and also keep the records of the product that is sold to the customers.
Development of an interactive car sale system which lets a user to find a car and its details is the main objective of this project. The administrators can access, enter, modify and delete the details of every car. Administrators are responsible of maintaining the details of vehicles like the Manufacturer information,
Python Project book shop system.This project BOOKSHOP SYSTEM includes some facilities for the retail book shop to maintain records of the books and also search, display, modification, delete etc the books available. This software searches the books data which is store in the record.
WHAT IS FUNCTION? WHY WE NEED FUNCTION.
TYPES OF FUNCTIONS
BUILT IN FUNCTIONS
int() , str(), float(), eval(), abs(),pow(), type() , round(),
modules in python,
Mat modules
pi, ceil(),pow(),floor(),sqrt(), sin(), cos() , tan()
NATURAL ENVIRONMENT,CATEGORIES OF RESOURCES,NATURAL RESOURCES,RENEWABLE AND NON-RENEWABLE,EXHAUSTIBLE , NON-EXHAUSTIBLE RESOURCES,HOW ENVIRONMENT IS CRUCIAL FOR US
WHAT IS DICTIONARY IN PYTHON?
HOW TO CREATE A DICTIONARY
INITIALIZE THE DICTIONARY
ACCESSING KEYS AND VALUES FROM A DICTIONARY
LOOPS TO DISPLAY KEYS AND VALUES IN A DICTIONARY
METHODS IN A DICTIONARY
TO WATCH VIDEO OR PDF:
https://computerassignmentsforu.blogspot.com/p/dictinpyxii.html
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
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
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Embracing GenAI - A Strategic ImperativePeter Windle
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.
2. In t his w e d isc uss a bo ut t he reading
wordsfrom a string.
to read word by word from a string
WORDS from the STRINGLet Us First read
3. Initialize string in a variable nmSTEP 1:
nm=“This Statement wORK FOR READing WORDS from the String in a variable”
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
4. Use split to break the words and store it
inside another variable and the length.
STEP 2:
word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split(): word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
k store the number of words in a variable word. It is 12
0 1 2 3 4 5 6 7 8 9 10 11
5. Now start the loop first case for read the words
using and for..range/while x start from 0 to k-1
STEP 3:
word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split(): word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
6. Next is display the wordsSTEP 4:
word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split(): word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
print(word,end=“”)
print(word[x],end=“”)
print(word[x],end=“”)
7. Move to next word in loopSTEP 5:
word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split(): word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
print(word,end=“”)
print(word[x],end=“”)
print(word[x],end=“”)
x=x+1Increment
automatically
Increment
automatically
This line use for
Incrementing value
8. So Now You know how to split() and read
words from a string.
Let Us
Solve some of the examples using same format
that we discuss to read words
Q1. Program to count number of words whose length is more than 5 or display those words
whose length is more than 5
9. Q1. Program to count number of words whose length is more than 5 or display those
words whose length is more than 5
word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split():
word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k):
x=0
while x<k:
print(word,end=“”)
print(word[x],end=“”)
print(word[x],end=“”)
x=x+1
10. Q1. Program to count number of words whose length is more than 5
word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split():
word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
print(word,end=“”)
print(word[x],end=“”)
print(word[x],end=“”)
x=x+1
First declare variable count=0 to count number of words whose length is more than 5
11. Q1. Program to count number of words whose length is more than 5
word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split():
word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
print(word,end=“”)
print(word[x],end=“”)
print(word[x],end=“”)
x=x+1
First declare variable count=0 to count number of words whose length is more than 5
12. Q1. Program to count number of words whose length is more than 5
word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split():
word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
print(word,end=“”)
print(word[x],end=“”)
print(word[x],end=“”)
x=x+1
First declare variable count=0 to count number of words whose length is more than 5
count=0
count=0 count=0
13. word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split():
word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
if len(word) > 5:
x=x+1
Next after for loop place if condition and check the length of the words are more
than 5 or not
count=0
count=0 count=0
if len(word[x]) > 5:
if len(word[x]) > 5:
14. word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split():
word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
if len(word) > 5:
x=x+1
After the if condition placed now put count inside if condition for countingcount
count=0
count=0 count=0
if len(word[x]) > 5:
if len(word[x]) > 5:
count=count+1
count=count+1
count=count+1
15. word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split():
word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
if len(word) > 5:
x=x+1
At last when all the words read and the check by if using len() and counting do no
we need to display how many words length more than 5
count=0
count=0 count=0
if len(word[x]) > 5:
if len(word[x]) > 5:
count=count+1
count=count+1
count=count+1print(“No of words more than 5:”,count)
print(“No of words more than 5:”,count)
print(“No of words more than 5:”,count)
16. word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split():
word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
if len(word) > 5:
x=x+1
count=0
count=0 count=0
if len(word[x]) > 5:
if len(word[x]) > 5:
count=count+1
count=count+1
count=count+1print(“No of words more than 5:”,count)
print(“No of words more than 5:”,count)
print(“No of words more than 5:”,count)
Q1. Program to display of words whose length is more than 5
First in this program remove the line of count=0 and count=count+1
17. word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split(): word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
if len(word) > 5:
x=x+1
if len(word[x]) > 5:
if len(word[x]) > 5:
print(“No of words more than 5:”,count)
print(“No of words more than 5:”,count)
print(“No of words more than 5:”,count)
Q1. Program to display of words whose length is more than 5
Now inside the if condition write the print line only and remove the last print
18. word=[‘This’,’Statement’,’wORK’,’FOR’,’READing’,’WORDS’,’from’,’the’,’String’,’in’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement wORK…..” nm=“This Statement wORK…..” nm=“This Statement wORK…..”
for word in nm.split(): word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
if len(word) > 5:
x=x+1
if len(word[x]) > 5:
if len(word[x]) > 5:
print(word)
Q1. Program to display of words whose length is more than 5
Now inside the if condition write the print line only and remove the last print
function also, there is no need of print count.
print(word[x])
print(word[x])
19. Let Us
discuss some of the examples using same format
that we discuss to read words
Q1. Program to count number of “that” in a string.
Q2. Program to count number of words whose first character is VOWEL.
Q3. Program to count number of words whose first character is UPPERCASE
Q4. Program to count number of words whose first character is LOWERCASE
Q5. Program to copy words whose first character is VOWEL in a another variable.
20. word=[‘This’,’Statement’,’that’,’FOR’,’READing’,’WORDS’,’that’,’the’,’String’,’that’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement that…..” nm=“This Statement that…..” nm=“This Statement that…..”
for word in nm.split():
word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
if word in “that”:
x=x+1
if word[x] in “that”:
if word[x] in “that”:
Inside If condition just check using == “that” to check that word exists
Q1. Program to count number of “that” in a string.
count=0
count=0 count=0
count=count+1
print(“No of that::”,count)
count=count+1
print(“No of that::”,count)
count=count+1
print(“No of that::”,count)
21. word=[‘This’,’Statement’,’that’,’FOR’,’READing’,’WORDS’,’that’,’the’,’String’,’that’,’a’,’variable’]
for….in for….range while ..loop
nm=“This Statement that…..” nm=“This Statement that…..” nm=“This Statement that…..”
for word in nm.split():
word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
if word “that”:
x=x+1
if word[x] “that”:
if word[x] “that”:
Q1. Program to count number of “that” in a string.
count=0
count=0 count=0
count=count+1
print(“No of that::”,count)
count=count+1
print(“No of that::”,count)
count=count+1
print(“No of that::”,count)
==
==
==
22. word=[‘This’,’Items’,’that’,’or’,’READing’,’Advance’,’that’,’the’,’String’,’that’,’a’,’variable’]
for….in for….range while ..loop
nm=“This items that…..” nm=“This items that…..” nm=“This items that…..”
for word in nm.split():
word=nm.split()
k=len(word)
word=nm.split()
k=len(word)
for x in range(0,k): x=0
while x<k:
if word[0] in “AEIOUaeiou”:
x=x+1
if word[x][0] in “AEIOUaeiou”:
count=0
count=0 count=0
count=count+1
print(“No of vowel:”,count)
count=count+1
print(“No of vowel:”,count)
count=count+1
print(“No of vowel:”,count)
Q2. Program to count number of words whose first character is VOWEL.
if word[x][0] in “AEIOUaeiou”: