BCA, Department of Information Technology teaches Python to Semester II students. The Curriculum of BCA JIMS is very well updated and as per the IT Industry. Admissions to BCA are open and students keen to do BCA have started applying.
To Apply for the best BCA College in Delhi NCR with the best Industry Interface you can visit www. jimssouthdelhi.com
Admission Open 2022, Apply Online
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Visit us at https://www.jimssouthdelhi.com/
BCA Course:https://www.jimssouthdelhi.com/course-bca.html
BCA Placements:https://www.jimssouthdelhi.com/bca-placement.html
BCA Admissions :https://www.jimssouthdelhi.com/admission-procedure.html
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COMPUTER SCIENCE SUPPORT MATERIAL CLASS 12.pdfrajkumar2792005
This document provides a list of group leaders and subject experts for preparation of support material for Class 12 Computer Science for the academic year 2023-24. It includes the names of 7 group leaders who are lecturers of Computer Science at different schools in Delhi, along with their school details. It also includes a table of contents listing the chapters and page numbers for the support material to be prepared. Key topics covered include Python revision, functions, exception handling, file handling, data structures, computer networks, database management systems, previous year and sample question papers, and 2 practice sets.
Values in Python can belong to different data types including numbers, strings, and lists. Numbers include integers, floating point numbers, and complex numbers. Strings are a sequence of characters that can be defined using single quotes, double quotes, or triple quotes. Common data types in Python include numbers, strings, lists, tuples, and dictionaries. Lists are mutable sequences while tuples are immutable sequences.
This document provides an overview of basic Python syntax and data types. It discusses indentation, statements, variables, numbers, strings, lists, tuples, and dictionaries. For each data type, it describes how to define, access, and manipulate objects of that type using various functions and methods. It also provides examples of working with each data type and exercises for hands-on practice. Overall, the document serves as a basic introduction to Python syntax and core data types for new programmers.
CS 360 LAB 3 STRINGS, FUNCTIONS, AND METHODSObjective The purpos.docxfaithxdunce63732
The document discusses Python strings, functions, and methods. It provides instructions for a lab exercise on evaluating string expressions and accessing substrings using indexing and slicing. It also introduces various Python data types like strings, lists, and numbers. The document compares Python to C and Java by discussing equivalent operations like variable assignment, data types, string concatenation, slicing, and deletion statements. It categorizes Python as having more flexible data types than C and Java.
This document provides an introduction and overview of the Python programming language course CSE 120 handled by G.Gandhi Jaba Kumar. It discusses that Python is an interpreted, object-oriented, and interactive programming language used for web development, software development, mathematics, and system scripting. The document then covers Python syntax including indentation, comments, keywords, variables, data types, operators, and basic programming concepts like conditionals and loops. It provides examples to illustrate Python code and best practices.
This document discusses Python programming concepts including data types, operators, expressions, and control flow. It covers core data types like integers, floats, strings, Booleans, lists, and tuples. It also describes arithmetic, comparison, assignment, logical, membership, and identity operators. Control flow concepts explained are if, if-elif-else, for, while loops, and statements like break, continue, and pass. The document is presented by B SNV Ramana Murthy of the computer science department at Aditya College of Engineering & Technology.
Python questions in pdf for data science interviews. A question bank on python for practice. In Reddit and Sanfoundry, you will get random questions, but here these are in order. The difficult to answer questions explained clearly.
COMPUTER SCIENCE SUPPORT MATERIAL CLASS 12.pdfrajkumar2792005
This document provides a list of group leaders and subject experts for preparation of support material for Class 12 Computer Science for the academic year 2023-24. It includes the names of 7 group leaders who are lecturers of Computer Science at different schools in Delhi, along with their school details. It also includes a table of contents listing the chapters and page numbers for the support material to be prepared. Key topics covered include Python revision, functions, exception handling, file handling, data structures, computer networks, database management systems, previous year and sample question papers, and 2 practice sets.
Values in Python can belong to different data types including numbers, strings, and lists. Numbers include integers, floating point numbers, and complex numbers. Strings are a sequence of characters that can be defined using single quotes, double quotes, or triple quotes. Common data types in Python include numbers, strings, lists, tuples, and dictionaries. Lists are mutable sequences while tuples are immutable sequences.
This document provides an overview of basic Python syntax and data types. It discusses indentation, statements, variables, numbers, strings, lists, tuples, and dictionaries. For each data type, it describes how to define, access, and manipulate objects of that type using various functions and methods. It also provides examples of working with each data type and exercises for hands-on practice. Overall, the document serves as a basic introduction to Python syntax and core data types for new programmers.
CS 360 LAB 3 STRINGS, FUNCTIONS, AND METHODSObjective The purpos.docxfaithxdunce63732
The document discusses Python strings, functions, and methods. It provides instructions for a lab exercise on evaluating string expressions and accessing substrings using indexing and slicing. It also introduces various Python data types like strings, lists, and numbers. The document compares Python to C and Java by discussing equivalent operations like variable assignment, data types, string concatenation, slicing, and deletion statements. It categorizes Python as having more flexible data types than C and Java.
This document provides an introduction and overview of the Python programming language course CSE 120 handled by G.Gandhi Jaba Kumar. It discusses that Python is an interpreted, object-oriented, and interactive programming language used for web development, software development, mathematics, and system scripting. The document then covers Python syntax including indentation, comments, keywords, variables, data types, operators, and basic programming concepts like conditionals and loops. It provides examples to illustrate Python code and best practices.
This document discusses Python programming concepts including data types, operators, expressions, and control flow. It covers core data types like integers, floats, strings, Booleans, lists, and tuples. It also describes arithmetic, comparison, assignment, logical, membership, and identity operators. Control flow concepts explained are if, if-elif-else, for, while loops, and statements like break, continue, and pass. The document is presented by B SNV Ramana Murthy of the computer science department at Aditya College of Engineering & Technology.
Python questions in pdf for data science interviews. A question bank on python for practice. In Reddit and Sanfoundry, you will get random questions, but here these are in order. The difficult to answer questions explained clearly.
This document provides an outline and overview of a presentation on learning Python for beginners. The presentation covers what Python is, why it is useful, how to install it and common editors used. It then discusses Python variables, data types, operators, strings, lists, tuples, dictionaries, conditional statements, looping statements and real-world applications. Examples are provided throughout to demonstrate key Python concepts and how to implement various features like functions, methods and control flow. The goal is to give attendees an introduction to the Python language syntax and capabilities.
Guido van Rossum emphasized the importance of code readability in Python. He introduced significant whitespace as a core feature of the language, aiming to enforce a clean and readable code structure. This emphasis on readability is evident in the presentation's mention of Python's design philosophy that highlights code readability.Van Rossum emphasized the importance of Python in enabling developers to write clear and logical code, which is scalable for both small and large-scale projects. The presentation mentions Python's language constructs and object-oriented approach designed to assist programmers in achieving this goal.
Though not explicitly attributed to van Rossum, Python's dynamically typed nature and built-in garbage collection contribute to its ease of use and simplification of memory management, reflecting the language's user-centric design principles.
Overall, Guido van Rossum's vision and design choices for Python resonate with the attributes and philosophies outlined in the presentation. His influence is seen in Python's core principles, which prioritize readability, versatility, and ease of use for programmers.
This document provides an overview of key concepts for data science in Python, including popular Python packages like NumPy and Pandas. It introduces Python basics like data types, operators, and functions. It then covers NumPy topics such as arrays, slicing, splitting and reshaping arrays. It discusses Pandas Series and DataFrame data structures. Finally, it covers operations on missing data and combining datasets using merge and join functions.
The document discusses Python programming concepts such as data types, variables, operators, and input/output. It provides examples of Python code and explains key features like:
- Python supports several data types including integers, floats, booleans, strings, and lists.
- Variables store and label values that can be of different data types. Variables are created using names.
- Operators like arithmetic, comparison, and logical operators are used to manipulate values.
- User input and output is handled through functions like print() and input().
- Comments, indentation, and quotation are syntax elements in Python code.
The document provides an overview of the Python programming language. It discusses what Python is, its history and naming, features like being dynamically typed and interpreted, popular applications like web development, machine learning, and its architecture. It also covers Python constructs like variables, data types, operators, and strings. The document compares Python to other languages and provides examples of common Python concepts.
This presentation is a great resource for zero-based Python programmers who wants to learn Python 3. This course includes brief history of Python and familiarity of its basic syntax.
Introduction to Python for Data Science and Machine Learning ParrotAI
This document provides an introduction and overview of Python for data science and machine learning. It covers basics of Python including what Python is, its features, why it is useful for data science. It also discusses installing Python, using the IDLE and Jupyter Notebook environments. The document then covers Python basics like variables, data types, operators, decision making and loops. Finally, it discusses collection data types like lists, tuples and dictionaries and functions in Python.
This document discusses strings in Python. It begins by defining strings as sequences of characters that can be represented using single or double quotes. It then discusses some key reasons why strings are important in programming, including text representation, input/output handling, and text processing. It also covers string literals, operations like repetition, membership, slicing, and concatenation. Finally, it discusses some real-world applications of strings like spell checkers, search engines, and information retrieval systems.
Python (Data Analysis) cleaning and visualizeIruolagbePius
This document provides an overview of Python programming language. It discusses Python features, uses, variables, data types, operators, decision making statements, and loops. Specifically, it covers:
- Python features like being easy to learn and read, having an interactive mode, and being portable.
- Python variables, naming rules, and basic data types like numbers, strings, booleans.
- Operators for arithmetic, comparison, assignment, and logic.
- Conditional statements like if, elif, else for decision making.
- Looping structures like while and for loops, with examples of using break, continue, else, range().
- How to write comments, take user input, and
The document discusses different data types in Python including numbers, strings, lists, tuples, and dictionaries. Numbers can be integers, floats, or complex. Integers do not have decimals while floats do. Lists and tuples are ordered sequences that can hold heterogeneous data types, but lists are mutable while tuples are immutable. Dictionaries are unordered collections of key-value pairs that provide efficient data retrieval. Strings are sequences of characters that can be represented using single or double quotes.
This document discusses basic data types in Python, including numeric, sequence, boolean, and dictionary types. It provides examples and explanations of integer, float, complex, string, list, tuple, set, and dictionary data types. Numeric types represent numeric values, sequence types organize ordered sequences, boolean represents True or False, and dictionary stores key-value pairs. Python assigns data types dynamically based on values and allows flexible conversion between types.
This document provides an overview of the Python programming language in 3 paragraphs. It discusses that Python is a high-level, interpreted, interactive and object-oriented scripting language. It was created by Guido van Rossum in the late 1980s and derived from languages like C and C++. The document then covers some key features of Python, including that it is easy to learn and read, portable, extensible and supports object-oriented programming. It provides examples of Python's basic syntax including indentation, variables, data types, operators and more.
This document discusses Python data types and keywords. It covers standard data types like numbers, strings, lists, tuples, dictionaries, booleans, and sets. It explains that Python automatically determines variable types and the type() function can check types. Keywords are reserved words in Python that have predefined meanings, like True, False, None, and, or, not, in, is for boolean logic and comparison. Other keywords include for, while, break, continue for iteration and try, except, finally, raise, assert for exception handling. The document provides examples and explanations of usage for different Python keywords.
This document discusses Python data types and keywords. It covers standard data types like numbers, strings, lists, tuples, dictionaries, booleans, and sets. It explains that Python automatically determines variable types and the type() function can check types. Keywords are reserved words in Python that have predefined meanings, like True, False, None, and, or, not, in, is for boolean logic and comparison. Other keywords include for, while, break, continue for iteration and try, except, finally, raise, assert for exception handling. The document provides examples and explanations of usage for different Python keywords.
Structured Languages- Need and Characteristics of OOP, Data Types and Modifiers, Arrays, Classes, Objects, Pointers, References, Difference between Pointers and References, Inheritance, Constructors, Destructors, and Polymorphism.
The document discusses Python data types and keywords. It covers standard data types like numbers, strings, lists, tuples, dictionaries, booleans and sets. It explains how to check data types and provides examples. It also discusses Python keywords like True, False, None, and, or, not, in and is. It covers keywords used for iteration like for, while, break and continue. Finally, it discusses exception handling keywords like try, except, finally and raise.
This document provides an introduction to Python programming concepts including data types, operators, control flow statements, functions and modules. It discusses the basic Python data types like integers, floats, booleans, strings, lists, tuples, dictionaries and sets. It also covers Python operators like arithmetic, assignment, comparison, logical and identity operators. Additionally, it describes control flow statements like if/else and for loops. Finally, it touches on functions, modules and input/output statements in Python.
This document provides information about a Python Programming course being taught in the first semester of an IT program. It includes the course title, code, class details, faculty name, date, course outcomes, topics covered, and module details. The module discusses Python container data types like lists, tuples, sets, and dictionaries. It provides examples and comparisons of the different data types. The document also covers topics like tuple comprehension, iterators, iterables, and dictionary comprehension.
These slides contain the concept of Macros. Macros in C Language are very powerful and used mostly to reduce the time and size of a code. It also allows reusing the code
JIMS BCA Curriculum includes Macros in Unit V of Programming Using C Subject.
JIMS provides an updated Curriculum and includes the concepts in depth.
Admission to BCA is Open.
https://www.jimssouthdelhi.com/admission-procedure.html
JIMS Vasant Kunj-II, BCA Department teaches Python in the Second Semester.
JIMS Vasant Kunj-II is one of the best BCA colleges in Delhi NCR.
BCA Admissions 2022 are Open. Interested Students can apply.
Visit us at https://www.jimssouthdelhi.com/
BCA Course:https://www.jimssouthdelhi.com/course-bca.html
BCA Placements:https://www.jimssouthdelhi.com/bca-placement.html
BCA Admissions :https://www.jimssouthdelhi.com/admission-procedure.html
Follow us on:
Facebook: https://www.facebook.com/JIMSVASANTKUNJII/
Twitter: https://twitter.com/jimsljptweets
Instagram : : https://www.instagram.com/jims_vk2/?hl=en
YouTube: https://www.youtube.com/channel/UCZgioa2rpculDY7bHlljD6g
Blog: https://jimssouthdelhi.com/blog/
Linked In: https://www.linkedin.com/in/jims-vasant-kunj-ii-38785a85/
This document provides an outline and overview of a presentation on learning Python for beginners. The presentation covers what Python is, why it is useful, how to install it and common editors used. It then discusses Python variables, data types, operators, strings, lists, tuples, dictionaries, conditional statements, looping statements and real-world applications. Examples are provided throughout to demonstrate key Python concepts and how to implement various features like functions, methods and control flow. The goal is to give attendees an introduction to the Python language syntax and capabilities.
Guido van Rossum emphasized the importance of code readability in Python. He introduced significant whitespace as a core feature of the language, aiming to enforce a clean and readable code structure. This emphasis on readability is evident in the presentation's mention of Python's design philosophy that highlights code readability.Van Rossum emphasized the importance of Python in enabling developers to write clear and logical code, which is scalable for both small and large-scale projects. The presentation mentions Python's language constructs and object-oriented approach designed to assist programmers in achieving this goal.
Though not explicitly attributed to van Rossum, Python's dynamically typed nature and built-in garbage collection contribute to its ease of use and simplification of memory management, reflecting the language's user-centric design principles.
Overall, Guido van Rossum's vision and design choices for Python resonate with the attributes and philosophies outlined in the presentation. His influence is seen in Python's core principles, which prioritize readability, versatility, and ease of use for programmers.
This document provides an overview of key concepts for data science in Python, including popular Python packages like NumPy and Pandas. It introduces Python basics like data types, operators, and functions. It then covers NumPy topics such as arrays, slicing, splitting and reshaping arrays. It discusses Pandas Series and DataFrame data structures. Finally, it covers operations on missing data and combining datasets using merge and join functions.
The document discusses Python programming concepts such as data types, variables, operators, and input/output. It provides examples of Python code and explains key features like:
- Python supports several data types including integers, floats, booleans, strings, and lists.
- Variables store and label values that can be of different data types. Variables are created using names.
- Operators like arithmetic, comparison, and logical operators are used to manipulate values.
- User input and output is handled through functions like print() and input().
- Comments, indentation, and quotation are syntax elements in Python code.
The document provides an overview of the Python programming language. It discusses what Python is, its history and naming, features like being dynamically typed and interpreted, popular applications like web development, machine learning, and its architecture. It also covers Python constructs like variables, data types, operators, and strings. The document compares Python to other languages and provides examples of common Python concepts.
This presentation is a great resource for zero-based Python programmers who wants to learn Python 3. This course includes brief history of Python and familiarity of its basic syntax.
Introduction to Python for Data Science and Machine Learning ParrotAI
This document provides an introduction and overview of Python for data science and machine learning. It covers basics of Python including what Python is, its features, why it is useful for data science. It also discusses installing Python, using the IDLE and Jupyter Notebook environments. The document then covers Python basics like variables, data types, operators, decision making and loops. Finally, it discusses collection data types like lists, tuples and dictionaries and functions in Python.
This document discusses strings in Python. It begins by defining strings as sequences of characters that can be represented using single or double quotes. It then discusses some key reasons why strings are important in programming, including text representation, input/output handling, and text processing. It also covers string literals, operations like repetition, membership, slicing, and concatenation. Finally, it discusses some real-world applications of strings like spell checkers, search engines, and information retrieval systems.
Python (Data Analysis) cleaning and visualizeIruolagbePius
This document provides an overview of Python programming language. It discusses Python features, uses, variables, data types, operators, decision making statements, and loops. Specifically, it covers:
- Python features like being easy to learn and read, having an interactive mode, and being portable.
- Python variables, naming rules, and basic data types like numbers, strings, booleans.
- Operators for arithmetic, comparison, assignment, and logic.
- Conditional statements like if, elif, else for decision making.
- Looping structures like while and for loops, with examples of using break, continue, else, range().
- How to write comments, take user input, and
The document discusses different data types in Python including numbers, strings, lists, tuples, and dictionaries. Numbers can be integers, floats, or complex. Integers do not have decimals while floats do. Lists and tuples are ordered sequences that can hold heterogeneous data types, but lists are mutable while tuples are immutable. Dictionaries are unordered collections of key-value pairs that provide efficient data retrieval. Strings are sequences of characters that can be represented using single or double quotes.
This document discusses basic data types in Python, including numeric, sequence, boolean, and dictionary types. It provides examples and explanations of integer, float, complex, string, list, tuple, set, and dictionary data types. Numeric types represent numeric values, sequence types organize ordered sequences, boolean represents True or False, and dictionary stores key-value pairs. Python assigns data types dynamically based on values and allows flexible conversion between types.
This document provides an overview of the Python programming language in 3 paragraphs. It discusses that Python is a high-level, interpreted, interactive and object-oriented scripting language. It was created by Guido van Rossum in the late 1980s and derived from languages like C and C++. The document then covers some key features of Python, including that it is easy to learn and read, portable, extensible and supports object-oriented programming. It provides examples of Python's basic syntax including indentation, variables, data types, operators and more.
This document discusses Python data types and keywords. It covers standard data types like numbers, strings, lists, tuples, dictionaries, booleans, and sets. It explains that Python automatically determines variable types and the type() function can check types. Keywords are reserved words in Python that have predefined meanings, like True, False, None, and, or, not, in, is for boolean logic and comparison. Other keywords include for, while, break, continue for iteration and try, except, finally, raise, assert for exception handling. The document provides examples and explanations of usage for different Python keywords.
This document discusses Python data types and keywords. It covers standard data types like numbers, strings, lists, tuples, dictionaries, booleans, and sets. It explains that Python automatically determines variable types and the type() function can check types. Keywords are reserved words in Python that have predefined meanings, like True, False, None, and, or, not, in, is for boolean logic and comparison. Other keywords include for, while, break, continue for iteration and try, except, finally, raise, assert for exception handling. The document provides examples and explanations of usage for different Python keywords.
Structured Languages- Need and Characteristics of OOP, Data Types and Modifiers, Arrays, Classes, Objects, Pointers, References, Difference between Pointers and References, Inheritance, Constructors, Destructors, and Polymorphism.
The document discusses Python data types and keywords. It covers standard data types like numbers, strings, lists, tuples, dictionaries, booleans and sets. It explains how to check data types and provides examples. It also discusses Python keywords like True, False, None, and, or, not, in and is. It covers keywords used for iteration like for, while, break and continue. Finally, it discusses exception handling keywords like try, except, finally and raise.
This document provides an introduction to Python programming concepts including data types, operators, control flow statements, functions and modules. It discusses the basic Python data types like integers, floats, booleans, strings, lists, tuples, dictionaries and sets. It also covers Python operators like arithmetic, assignment, comparison, logical and identity operators. Additionally, it describes control flow statements like if/else and for loops. Finally, it touches on functions, modules and input/output statements in Python.
This document provides information about a Python Programming course being taught in the first semester of an IT program. It includes the course title, code, class details, faculty name, date, course outcomes, topics covered, and module details. The module discusses Python container data types like lists, tuples, sets, and dictionaries. It provides examples and comparisons of the different data types. The document also covers topics like tuple comprehension, iterators, iterables, and dictionary comprehension.
These slides contain the concept of Macros. Macros in C Language are very powerful and used mostly to reduce the time and size of a code. It also allows reusing the code
JIMS BCA Curriculum includes Macros in Unit V of Programming Using C Subject.
JIMS provides an updated Curriculum and includes the concepts in depth.
Admission to BCA is Open.
https://www.jimssouthdelhi.com/admission-procedure.html
JIMS Vasant Kunj-II, BCA Department teaches Python in the Second Semester.
JIMS Vasant Kunj-II is one of the best BCA colleges in Delhi NCR.
BCA Admissions 2022 are Open. Interested Students can apply.
Visit us at https://www.jimssouthdelhi.com/
BCA Course:https://www.jimssouthdelhi.com/course-bca.html
BCA Placements:https://www.jimssouthdelhi.com/bca-placement.html
BCA Admissions :https://www.jimssouthdelhi.com/admission-procedure.html
Follow us on:
Facebook: https://www.facebook.com/JIMSVASANTKUNJII/
Twitter: https://twitter.com/jimsljptweets
Instagram : : https://www.instagram.com/jims_vk2/?hl=en
YouTube: https://www.youtube.com/channel/UCZgioa2rpculDY7bHlljD6g
Blog: https://jimssouthdelhi.com/blog/
Linked In: https://www.linkedin.com/in/jims-vasant-kunj-ii-38785a85/
BCA Department of Information Technology, JIMS Vasant Kunj-II teaches Java Language in IVth Semester. The Course Curriculum is very well updated. This PDF includes the details of Topic Polymorphism. Students should read it. JIMS Vasant Kunj-II provides the best BCA Course in Delhi NCR. The BCA Admission 2022 is open.
BCA, Department of Information Technology and Software Development teaches JAVA Language in the fourth semester. The curriculum of the BCA Course of JIMS is very well updated. In this PDF, the Constructor topic is explained. It is one of the very important Concepts and you need to understand it thoroughly.
BCA Department of Software Development and Information Technology shares the detail of Eclipse GUI Pallete and its configuration.
JIMS Vasant Kunj-II is the best BCA College in Delhi NCR. It provides the best BCA Course Curriculum and Top Placements.
The Faculties of the BCA department teach all languages in the latest tools, demand in the IT Companies and used by all Software Developers.
Eclise is one of the most demanding tools and we teach to BCA IV and V semester students. The curriculum includes Java, Advance Java, and web technologies.
Students kindly go through these details.
BCA Admissions are open, interested students can visit our website www.jimssouthdelhi.com
BCA, Department of Information Technology and Software Development teaches Java and Advanced Java in the Third and Fifth semesters. The best part of the Department faculties is to teach the software in the latest tool, which is used by the IT Experts in the software Companies. We teach Java and Advance Java in Eclipse, Net Beans, and IntelliJ.
JIMS Vasant Kunj-II provides the best BCA Course. This is one of the best BCA colleges in Delhi NCR. The admissions 2022 is open and interested students can apply.
www.jimssouthdelhi.com
We at JIMS Vasant Kunj-II use the latest tools to use all the latest languages we included in the curriculum.
Our BCA Curriculum is well updated as per the Industry Demand and standards.
BCA Department of JIMS Vasant Kunj-II, teaches C language in Semester 1. Here Dr. Arpana Chaturvedi shares the concept of Two Dimensional Array. It is in Unit II.
JIMS VasantKunj-II is one of the bestBCACollegeinDelhiNCR. The Course Content of BCA is as per the technology in demand and well updated.
There are two types of Arrays, in this pdf, a two-dimensional array is described. The Document explains well the concept with examples of Two Dimensional Array
BCA, JIMS Vasant Kunj-II teaches C language to First Semester students. In this pdf, you can read the fundamentals of Array. JIMS Vasant Kunj-II is one of the best BCA colleges in Delhi NCR with an updated Curriculum.
Machine Learning: Need of Machine Learning, Its Challenges and its ApplicationsArpana Awasthi
BCA Department of JIMS Vasant Kunj-II is one of the best BCA colleges in Delhi NCR. The curriculum is well updated and the subjects included all the latest technologies which are in demand.
JIMS BCA course teaches Python to II semester students and Artificial Intelligence Using Python to Sixth Semester students.
Here is a small article on the Future of Machine Learning, hope you will find it useful.
Machine Learning is a field of Computer science in which computer systems are able to learn from past experiences, examples, environments. With help of various Machine Learning Algorithms, Computers are provided with the ability to sense the data and produce some relevant results.
Machine learning Algorithms provide the technique of predicting the future outcomes or classifying information from the given input to the Machines so that the appropriate decisions can be taken.
JIMS Vasant Kunj-II is one of the best BCA colleges in Delhi NCR. The Course content provided to BCA students are well updated and as per the Demand of the IT Industry. It helps to get Placements in Top IT Companies.
This Pdf includes the Details of File Handling in C. This comes in Unit IV.
JIMS is one of the best BCA colleges in Delhi NCR. The Curriculum they provide to the BCA students is well updated. So many activities are for BCA students like Guest Lectures from the IT Experts, Workshops, IT Activities, Annual IT Events, Emphasise on Research work and project Work. In this pdf, Dr. Arpana talks about various types of Programming Languages a BCA student should be aware of different Languages.
Role of machine learning in detection, prevention and treatment of cancerArpana Awasthi
Author: Dr. Arpana Chaturvedi (Jagannath International Management School, New Delhi, ac240871@gmail.com)
Artificial Intelligence, Machine Learning and Deep Learning now-a-days started playing its very effective and important role resulting great impact on various domains. These fields have been used in all areas as Data scientists realized that with the strength and power of rapidly growing data. The data shared by people of all ages in almost all social media handlers is of different types and in huge volume. This data consists of various kind of information related to almost all domains. Data analyst knows the power of this data and they introduced various techniques to get fruitful hidden insights from the data to benefit various organizations.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
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Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
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* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
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#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
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Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
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Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
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Neha Bajwa, Vice President of Product Marketing, Neo4j
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Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
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We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
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• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
1. Jagannath Institute of Management Sciences
Vasant Kunj-II, New Delhi - 110070
Subject Name: BVITSD 205 : Programming And
Problem Solving Though PYTHON
Department of Information Technology
Created By: Dr. Arpana Chaturvedi
@Dr. Arpana Chaturvedi
2. Subject: BVITSD 205 : PROGRAMMING AND
PROBLEM SOLVING THOUGH PYTHON
Topic: Unit II- Python Variables and Data Types
@Dr. Arpana Chaturvedi
3. Unit-II Python Variables and Data Types
@Dr. Arpana Chaturvedi
An Introduction to
Variables
Data Types
Types
Conversion
Local and
Global
Variables
Variable Naming
Rules
Assigning
Variables
Numbers
Strings
int()
float()
Local
Variables
Global
Variables
str()
bool()
list()
List
Tuple
Dictionaries
Multiple
Variables
Deleting
Variables
4. Unit-II Python Variables
@Dr. Arpana Chaturvedi
Python Variables
X=45
Type=Integer
name=“ JIMS ”
Type=String
nums=[ 1,3,5,7 ] Type=Lists
45
x
“ JIMS ”
name
[ 1,3,5,7 ]
nums
▰ A variable is a container for a value. It can be assigned a name, you can use it to
refer to it later in the program.
▰ Based on the value assigned, the interpreter decides its data type. You can always
store a different type in a variable.
5. Unit-II Python Variable Naming Convention
There are certain rules to what you can name a variable(called an identifier).
▰ Python variables can only begin with a letter(A-Z/a-z) or an underscore(_).
▰ The rest of the identifier may contain letters(A-Z/a-z), underscores(_), and
numbers(0-9).
▰ Python is case-sensitive, and so are Python identifiers. Name and name are two
different identifiers.
▰ Reserved words (keywords) cannot be used as identifier names.
@Dr. Arpana Chaturvedi
7. Unit-II 2. Assigning and Reassigning Python
Variables
▰ To assign a value to Python variables, you don‟t need to declare its type.
▰ You name it according to the rules of variable naming convention, and type the
value after the equal sign(=).
@Dr. Arpana Chaturvedi
You can‟t put the identifier on the right-hand side of the equal sign, though. The
following code causes an error.
Neither can you assign Python variables to a keyword.
8. Unit-II 3. Multiple Assignment
▰ You can assign values to multiple Python variables in one statement.
▰ Or you can assign the same value to multiple Python variables.
@Dr. Arpana Chaturvedi
9. Unit-II 4. Swapping Python Variables
▰ Swapping means interchanging values. To swap Python variables, you don‟t need
to do much.
@Dr. Arpana Chaturvedi
10. Unit-II 4.Deleting Python Variables
▰ You can also delete Python variables using the keyword „del‟.
@Dr. Arpana Chaturvedi
11. Unit-II Python Datatypes
▰ Although we don‟t have to declare a type for Python variables, a value does have a
type. This information is vital to the interpreter.
▰ Python supports the following data types.
1. Python Numbers
2. Strings
3. Python Lists
4. Python Tuples
5. Dictionaries
7. Sets
@Dr. Arpana Chaturvedi
12. Unit-II 1. Python Numbers
▰ There are four numeric Python data types.
a. int
b. float
c. long
d. complex
@Dr. Arpana Chaturvedi
13. Unit-II 1. Python Numbers
a. int
▰ int stands for integer. This Python Data Type holds signed integers. We can use the
type() function to find which class it belongs to.
@Dr. Arpana Chaturvedi
An integer can be of any length, with the only limitation being the available memory.
14. Unit-II 1. Python Numbers
b. float
▰ This Python Data Type holds floating-point real values. An int can only store the
number 3, but float can store 3.25 if you want.
@Dr. Arpana Chaturvedi
c. long
This Python Data type holds a long integer of unlimited length. But this construct does
not exist in Python 3.x.
15. Unit-II 1. Python Numbers
d. complex
This Python Data type holds a complex number. A complex number looks like this: a+bj
Here, a and b are the real parts of the number, and j is imaginary.
@Dr. Arpana Chaturvedi
Use the isinstance() function to tell if Python variables belong to a particular class. It
takes two parameters- the variable/value, and the class.
16. Unit-II 2. Strings
▰ A String is a sequence of characters. Python does not have a char data type, unlike
C++ or Java. You can delimit a string using single quotes or double-quotes.
@Dr. Arpana Chaturvedi
a. Spanning a String Across Lines
▰ To span a string across multiple lines, you can use triple quotes.
As you can see, the quotes
preserved the formatting (n is the
escape sequence for newline, t is
for tab).
17. Unit-II 2. Strings
@Dr. Arpana Chaturvedi
b. Displaying Part of a String
You can display a character from a string using its index in the string. Remember,
indexing starts with 0.
You can also display a burst of characters in a string using the slicing operator [].
This prints the characters from 0 to 5.
18. Unit-II 2. Strings
@Dr. Arpana Chaturvedi
c. String Formatters
String formatters allow us to print characters and values at once. You can use the %
operator.
Or you can use the format method.
A third option is to use f-strings.
19. Unit-II 2. Strings
@Dr. Arpana Chaturvedi
d. String Concatenation
You can concatenate(join) strings.
However, you cannot concatenate values of different types.
20. Unit-II 3. Python Lists
@Dr. Arpana Chaturvedi
A list is a collection of values. Remember, it may contain different types of values.
To define a list, you must put values separated with commas in square brackets. You
don‟t need to declare a type for a list either.
a. Slicing a List
You can slice a list the way you‟d slice a string- with the slicing operator.
Indexing for a list begins with 0, like for a string. A Python doesn‟t have arrays.
21. Unit-II 3. Python Lists
@Dr. Arpana Chaturvedi
c. Length of a List
Python supports an inbuilt function to calculate the length of a list.
c. Reassigning Elements of a List
A list is mutable. This means that you can reassign elements later on.
22. Unit-II 3. Python Lists
@Dr. Arpana Chaturvedi
d. Iterating on the List
To iterate over the list we can use the for loop. By iterating, we can access each
element one by one which is very helpful when we need to perform some operations
on each element of list.
23. Unit-II 3. Python Lists
@Dr. Arpana Chaturvedi
e. Multidimensional Lists
A list may have more than one dimension.
24. Unit-II Python Tuples
▰ A tuple is like a list. You declare it using parentheses instead.
@Dr. Arpana Chaturvedi
a. Accessing and Slicing a Tuple
You access a tuple the same way as you‟d access a list. The same goes for slicing
it.
25. Unit-II Python Tuples
@Dr. Arpana Chaturvedi
b. A tuple is Immutable
Python tuple is immutable. Once declared, you can‟t change its size or elements.
26. Unit-II 5. Dictionaries
▰ A dictionary holds key-value pairs. Declare it in curly braces, with pairs separated
by commas. Separate keys and values by a colon(:).
▰ The type() function works with dictionaries too.
@Dr. Arpana Chaturvedi
27. Unit-II 5. Dictionaries
▰ a. Accessing a Value
▰ To access a value, you mention the key in square brackets.
▰ b. Reassigning Elements
▰ You can reassign a value to a key.
@Dr. Arpana Chaturvedi
28. Unit-II 5. Dictionaries
▰ c. List of Keys
▰ Use the keys() function to get a list of keys in the dictionary.
@Dr. Arpana Chaturvedi
29. Unit-II 6. bool
▰ A Boolean value can be True or False.
@Dr. Arpana Chaturvedi
30. Unit-II 7. Sets
▰ 7. Sets
▰ A set can have a list of values. Define it using curly braces.
@Dr. Arpana Chaturvedi
It returns only one instance of any value present more than once.
However, a set is unordered, so it doesn‟t support indexing.
31. Unit-II 7. Sets
▰ 7. Sets
▰ Also, it is mutable. You can change its elements or add more. Use the add() and
remove() methods to do so.
@Dr. Arpana Chaturvedi
32. Unit-II Python Type Conversion
▰ Since Python is dynamically-typed, you may want to convert a value into another
type. Python supports a list of functions for the same.
▰ 1. int()
▰ It converts the value into an int.
@Dr. Arpana Chaturvedi
Notice how it truncated 0.7 instead of rounding the number off to 4. You can also turn
a Boolean into an int.
33. Unit-II Python Type Conversion
▰ However, you cannot turn a string into an int. It throws an error.
@Dr. Arpana Chaturvedi
However, if the string has only numbers, then you can.
34. Unit-II Python Type Conversion
▰ 2. float()
▰ It converts the value into a float.
@Dr. Arpana Chaturvedi
However, this number works even without the float() function.
You can also use ‘e’ to denote an exponential number.
35. Unit-II Python Type Conversion
▰ 3. str()
▰ It converts the value into a string.
@Dr. Arpana Chaturvedi
36. Unit-II Python Type Conversion
▰ 4. bool()
▰ It converts the value into a Boolean.
@Dr. Arpana Chaturvedi
37. Unit-II 5. Python Sets
▰ 5. set()
▰ It converts the value into a set.
@Dr. Arpana Chaturvedi
38. Unit-II 6. Python list()
▰ 6. list()
▰ It converts the value into a list.
@Dr. Arpana Chaturvedi
39. Unit-II 7. Python tuple
▰ 7. tuple()
▰ It converts the value into a tuple.
@Dr. Arpana Chaturvedi
You can try your own combinations. Also
try composite functions.
40. Unit-II Python Local and Global Variables
▰ 1. Python Local Variables
▰ When you declare a variable in a function, class, or so, it is only visible in that
scope. If you call it outside of that scope, you get an „undefined‟ error.
@Dr. Arpana Chaturvedi
Here, the variable num is local to function func1().
41. Unit-II Python Local and Global Variables
▰ 2. Global Variables
▰ When you declare a variable outside any context/scope, it is visible in the whole
program.
@Dr. Arpana Chaturvedi
42. Unit-II Python Local and Global Variables
▰ 2. Global Variables
▰ You can use the „global‟ keyword when you want to treat a variable as global in a
local scope.
@Dr. Arpana Chaturvedi
43. Unit-II Python Variables Assignment
▰ What are variables and data types in Python?
▰ What is type () in Python?
▰ What are Local and Global variables in Python?
▰ Explain various naming rules for Python Variables.
▰ How to display part of a string?
@Dr. Arpana Chaturvedi