this guidebook contains almost all types of links to useful stuff, courses, programs to learn and enhance technical skills. it will help those students who want to pursue their career in programming.
The document outlines the courses offered in the 5th semester of the Master of Computer Applications program at Sona College of Technology in Salem for the 2015 regulations. It lists 5 elective courses on topics such as e-learning techniques, wireless sensor networks, software project management, management information systems, and object oriented analysis and design. It also lists 3 mandatory courses on cloud computing, C# and .NET programming, and a cloud computing laboratory. For each course, it provides information on course objectives, topics covered, course outcomes, and references. It approves the course structure and regulations and specifies they were approved by the chairpersons and members of the relevant academic bodies.
The document provides information about an upcoming Google Developer Student Club (GDSC) event at KMIT. It introduces the GDSC program and describes how students can learn new skills through hands-on workshops, projects and interacting with other developers. The core team leading the KMIT GDSC chapter is introduced. Upcoming events on cloud computing, Flutter, artificial intelligence/machine learning and web development are briefly outlined. Students are encouraged to join the GDSC community to enhance their skills and career opportunities.
Microsoft azure certification training courseBhupalApponix
With the help of this course, you can be a part of the Azure revolution. This Azure course is best appropriate for individuals who want to succeed in their career as an Azure Administrator and is aligned with the Examination AZ-104 Microsoft Azure Administrator (2020 Edition).
The document outlines a 30 Days of Google Cloud program that aims to prepare students for cloud careers. It discusses two tracks - Cloud Engineering and Data Science & Machine Learning. Students can get hands-on training using Qwiklabs and earn skill badges. Upon completing all challenges, they will receive a certificate from Google along with other rewards and prizes. The timeline shows the program kicking off on September 26th with student enrollment until September 31st and track completions deadline on November 5th.
Abhishek Yadav is an undergraduate student at MIT College of Engineering in Pune, India studying computer engineering. His philosophy is to make improvements rather than excuses. He is most proud of conducting seminars and workshops on cyber security and ethical hacking. His strengths include being hard-working, never giving up, being a motivator and leader, being self-confident, and being a team worker. He has experience in C++, Python, Linux, cyber security, AWS, IOT, and data analysis. His interests include aviation, sports, travel, video editing, and Indian politics. He has worked as an intern and core team member at H@ckedemist on various cyber security and cloud projects.
This document is a resume for Muhammad Khalid. It summarizes his contact information, objective, education history, professional experience working as a PHP web developer since 2008, skills including PHP, Drupal, MySQL, and Android development, completed projects, and websites developed.
This document describes a 30-day program for learning Google Cloud called #30DaysofGoogleCloud. The program includes two tracks - Cloud Engineering and Data Science & Machine Learning. Each track involves completing 6 skill badges that involve tasks like creating and managing cloud resources, deploying to Kubernetes, and exploring machine learning models. Completing the program earns a certificate of completion from Google along with skill badges and other rewards. The document provides background on cloud computing and an overview of Google Cloud Platform and how to interact with it.
The document outlines the courses offered in the 5th semester of the Master of Computer Applications program at Sona College of Technology in Salem for the 2015 regulations. It lists 5 elective courses on topics such as e-learning techniques, wireless sensor networks, software project management, management information systems, and object oriented analysis and design. It also lists 3 mandatory courses on cloud computing, C# and .NET programming, and a cloud computing laboratory. For each course, it provides information on course objectives, topics covered, course outcomes, and references. It approves the course structure and regulations and specifies they were approved by the chairpersons and members of the relevant academic bodies.
The document provides information about an upcoming Google Developer Student Club (GDSC) event at KMIT. It introduces the GDSC program and describes how students can learn new skills through hands-on workshops, projects and interacting with other developers. The core team leading the KMIT GDSC chapter is introduced. Upcoming events on cloud computing, Flutter, artificial intelligence/machine learning and web development are briefly outlined. Students are encouraged to join the GDSC community to enhance their skills and career opportunities.
Microsoft azure certification training courseBhupalApponix
With the help of this course, you can be a part of the Azure revolution. This Azure course is best appropriate for individuals who want to succeed in their career as an Azure Administrator and is aligned with the Examination AZ-104 Microsoft Azure Administrator (2020 Edition).
The document outlines a 30 Days of Google Cloud program that aims to prepare students for cloud careers. It discusses two tracks - Cloud Engineering and Data Science & Machine Learning. Students can get hands-on training using Qwiklabs and earn skill badges. Upon completing all challenges, they will receive a certificate from Google along with other rewards and prizes. The timeline shows the program kicking off on September 26th with student enrollment until September 31st and track completions deadline on November 5th.
Abhishek Yadav is an undergraduate student at MIT College of Engineering in Pune, India studying computer engineering. His philosophy is to make improvements rather than excuses. He is most proud of conducting seminars and workshops on cyber security and ethical hacking. His strengths include being hard-working, never giving up, being a motivator and leader, being self-confident, and being a team worker. He has experience in C++, Python, Linux, cyber security, AWS, IOT, and data analysis. His interests include aviation, sports, travel, video editing, and Indian politics. He has worked as an intern and core team member at H@ckedemist on various cyber security and cloud projects.
This document is a resume for Muhammad Khalid. It summarizes his contact information, objective, education history, professional experience working as a PHP web developer since 2008, skills including PHP, Drupal, MySQL, and Android development, completed projects, and websites developed.
This document describes a 30-day program for learning Google Cloud called #30DaysofGoogleCloud. The program includes two tracks - Cloud Engineering and Data Science & Machine Learning. Each track involves completing 6 skill badges that involve tasks like creating and managing cloud resources, deploying to Kubernetes, and exploring machine learning models. Completing the program earns a certificate of completion from Google along with skill badges and other rewards. The document provides background on cloud computing and an overview of Google Cloud Platform and how to interact with it.
This document provides an overview of machine learning and data science using Python. It introduces machine learning and data science, the Python programming language, popular integrated development environments for Python, and Google Colab. It also discusses types of machine learning algorithms, the machine learning process, important Python libraries, the data science life cycle, data visualization techniques, and the differences between machine learning and data science. The document outlines how to use Google Colab for machine learning and data science projects and provides information on the scope and applications of machine learning and data science.
Teaching Machine Learning with Physical Computing - July 2023Hal Speed
This document provides an overview of resources for teaching machine learning and artificial intelligence concepts to K-12 students. It discusses machine learning concepts and workflows. It then lists and briefly describes various hardware platforms, software tools, curricula, and online resources that can be used to teach machine learning, including platforms for visual programming languages like Scratch and Blockly.
Delivered at Pittsburgh Tech Fest - 6/10/2017
Knowledge is power, but is it if you're not using it? What if the application you delivered to your customers was extremely intelligent? It could retrieve, analyze and use the massive amounts of data that businesses are generating at an astronomical rate.
It could analyze business deals, predict potential issues, proactively recommend business decisions and estimate profit, loss and risks.
Those things provide direct benefits to your company. Churning through that data by hand doesn't. Enter Azure Machine Learning.
In this session you will learn how to integrate Azure Machine Learning into your existing applications and workflows with REST services. You will learn how to deliver a modular, maintainable solution to your customers that allows them to analyze their data.
You will learn to:
* Numerous ways to abstract business rules, workflows, AI (Machine Learning) and more into your applications
* How to Integrate Azure Machine Learning into your existing Applications and Processes
* Create Azure Machine Learning Experiments
* Retrieve the Score from an Azure Machine Learning Experiment and integrate it into your applications and processes
* Integrate numerous Machine Learning Experiments from the Azure Machine Learning Marketplace into your existing applications and processes
* Learn various concepts for abstracting and managing services and api's.
Java Tech Day 2009 - Developing Cloud Computing Applications With JavaShlomo Swidler
Challenges faced by developers of cloud-computing applications and Java-based solutions. Including an overview of Google App Engine, Amazon Web Services, and sample Java code demonstrating design patterns that will scale in the cloud.
This document provides information about a 30 Days of Google Cloud program being run by GDSC and RobSoc at Miranda House, University of Delhi. The summary includes:
- The program aims to help participants unlock benefits and gain hands-on experience in Google Cloud over 30 days by completing skill badges and tracks in cloud engineering and data science/machine learning.
- Participants can choose to complete one track for rewards, or both tracks for additional rewards, including a certificate of appreciation from Google and goodies.
- The program will provide training to help participants earn skill badges by completing hands-on labs and assessments to demonstrate their cloud skills.
Delivered @ MusicCityCode 6/2/2017
Knowledge is power, but is it if you're not using it? What if the application you delivered to your customers was extremely intelligent? It could retrieve, analyze and use the massive amounts of data that businesses are generating at an astronomical rate.
It could analyze business deals, predict potential issues, proactively recommend business decisions and estimate profit, loss and risks.
Those things provide direct benefits to your company. Churning through that data by hand doesn't. Enter Azure Machine Learning.
In this session you will learn how to integrate Azure Machine Learning into your existing applications and workflows with REST services. You will learn how to deliver a modular, maintainable solution to your customers that allows them to analyze their data.
You will learn to:
* Numerous ways to abstract business rules, workflows, AI (Machine Learning) and more into your applications
* How to Integrate Azure Machine Learning into your existing Applications and Processes
* Create Azure Machine Learning Experiments
* Retrieve the Score from an Azure Machine Learning Experiment and integrate it into your applications and processes
* Integrate numerous Machine Learning Experiments from the Azure Machine Learning Marketplace into your existing applications and processes
* Learn various concepts for abstracting and managing services and api's.
The document provides a 12-step roadmap for becoming a data engineer, including recommended courses, books, and hands-on projects for skills like computer science fundamentals, programming with Python and SQL, Linux, big data systems, data warehousing, batch and stream processing, cloud computing, data orchestration with Airflow, and data engineering management. It also shares additional learning resources like blogs, podcasts, conferences, YouTube channels, and people to follow on social media to continue expanding data engineering knowledge.
Karshil Sheth is a computer science student from Indus University in Ahmedabad, India with experience in web development, Java, and databases. He has worked as an intern at multiple companies developing websites, applications, and databases using technologies like Java, PHP, HTML, CSS, and MySQL. He is skilled in languages like Java, Python, C++, and databases like MySQL, Oracle, and has certifications in Java and training in technologies like C, C++, Python, and Hadoop.
This document outlines the syllabus for an Advanced Computer Networks course. It includes the following key points:
1. The course is taught by Dr. S. Sridevi and covers milestones in conventional networking, software defined networking (SDN), and applications of artificial intelligence and machine learning algorithms to network management, security, and data analysis.
2. The pre-requisite for the course is an Introduction to Computer Networks course.
3. The course outcomes are for students to understand conventional and SDN, implement SDNs using Mininet and Raspberry Pi, and understand network management and security using AI/ML algorithms.
GCSJ 2023 is a fantastic opportunity to immerse yourself in Google Cloud technologies ☁️. Whether you're a beginner or an experienced cloud practitioner, this session will be a stepping stone to enter the world of cloud computing.
This document provides information about courses for a Bachelor of Technology in Computer Science and Engineering for Semester VIII. It lists 5 required courses covering topics like project work, electives in professional and open electives, and corresponding labs. Details are provided for each course including credit hours, examination scheme, topics covered and suggested reading materials. The document also outlines the eligibility criteria for elective courses.
This document provides information about the Google Developer Student Club (GDSC) at the Faculty of Engineering and Technology, Jain University. It introduces the community leaders and faculty advisor. It summarizes the accomplishments of GDSC in the previous year. It then describes the benefits of joining GDSC such as learning skills, accessing Google resources, networking opportunities, and completing milestones to earn schwags.
The document outlines the 30 Days of Google Cloud program that GDSC will run, including the two tracks of Cloud Engineering and Data Science & Machine Learning. It lists the topics that will be covered in each track and the timeline for student registration, the campaign, and rewards distribution. Completing one track earns participants
The document discusses how cloud computing can transform military training and education. It begins by defining cloud computing and describing its key attributes such as scalability, reliability, and low cost. It then outlines how the cloud could benefit the enterprise through cost-effective infrastructure, empower instructors to create and share content, and tailor training to individual trainees' careers. The implications of cloud delivery and analytics are examined, including cloud gaming and simulation as well as using big data and machine learning to analyze training outcomes. Finally, the document argues that organizations should develop a cloud strategy to unify isolated training systems and take advantage of the cloud's potential to streamline infrastructure and make training more data-driven.
End To End Machine Learning With Google Cloud Tu Pham
This document discusses end-to-end machine learning with Google Cloud. It outlines an 8-step process for collecting raw data, converting it to Apache Parquet files, uploading it to Cloud Storage, exploring it in Datalab, developing models in TensorFlow/Scikit-learn, training models at scale on Cloud ML Engine, deploying models via APIs on Compute Engine, and exposing APIs with Load Balancing. Key principles discussed are keeping it simple, avoiding repetition, and focusing on scalability, performance, and cost optimization. The presenter encourages planning systems with single responsibilities, separating real-time and batch flows, and saving on networking, instance, and storage costs through monitoring.
The document outlines a 90-hour summer training course on Internet of Things (IoT) with real-time application projects. The training will take place in June 2018 in Faridabad, India and cover 11 modules, including introductions to IoT, sensor technologies, programming with Python, cloud computing models, IoT security issues, and industrial IoT systems. Hands-on sessions will focus on interfacing sensors like temperature, humidity, and ultrasonic range finders with Raspberry Pi kits and developing IoT projects around environmental monitoring, security, and home automation. The schedule provides duration and learning objectives for each module.
This course introduces students to cloud computing, artificial intelligence, and decentralized applications technologies. Students will learn about major cloud platforms and related services for computing, storage, networking, big data, and machine learning. They will combine these services to create intelligent autonomous networked solutions. The course also covers decentralized computing using Ethereum, smart contracts, and developing decentralized applications. Students will build their own projects combining cloud and decentralized technologies.
This document provides an overview of IBM's cloud platforms and services for developing applications. It discusses IBM Bluemix as a Platform as a Service (PaaS) that allows deploying apps quickly using managed infrastructure. Bluemix embraces Cloud Foundry and provides over 160 services for building apps. The IBM IoT Foundation is also summarized as connecting devices to send data to the cloud and build apps accessing that device data through APIs. The document promotes signing up for a free Bluemix trial and finding open datasets and APIs to use for app development.
A Strategic Approach: GenAI in EducationPeter 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.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
This document provides an overview of machine learning and data science using Python. It introduces machine learning and data science, the Python programming language, popular integrated development environments for Python, and Google Colab. It also discusses types of machine learning algorithms, the machine learning process, important Python libraries, the data science life cycle, data visualization techniques, and the differences between machine learning and data science. The document outlines how to use Google Colab for machine learning and data science projects and provides information on the scope and applications of machine learning and data science.
Teaching Machine Learning with Physical Computing - July 2023Hal Speed
This document provides an overview of resources for teaching machine learning and artificial intelligence concepts to K-12 students. It discusses machine learning concepts and workflows. It then lists and briefly describes various hardware platforms, software tools, curricula, and online resources that can be used to teach machine learning, including platforms for visual programming languages like Scratch and Blockly.
Delivered at Pittsburgh Tech Fest - 6/10/2017
Knowledge is power, but is it if you're not using it? What if the application you delivered to your customers was extremely intelligent? It could retrieve, analyze and use the massive amounts of data that businesses are generating at an astronomical rate.
It could analyze business deals, predict potential issues, proactively recommend business decisions and estimate profit, loss and risks.
Those things provide direct benefits to your company. Churning through that data by hand doesn't. Enter Azure Machine Learning.
In this session you will learn how to integrate Azure Machine Learning into your existing applications and workflows with REST services. You will learn how to deliver a modular, maintainable solution to your customers that allows them to analyze their data.
You will learn to:
* Numerous ways to abstract business rules, workflows, AI (Machine Learning) and more into your applications
* How to Integrate Azure Machine Learning into your existing Applications and Processes
* Create Azure Machine Learning Experiments
* Retrieve the Score from an Azure Machine Learning Experiment and integrate it into your applications and processes
* Integrate numerous Machine Learning Experiments from the Azure Machine Learning Marketplace into your existing applications and processes
* Learn various concepts for abstracting and managing services and api's.
Java Tech Day 2009 - Developing Cloud Computing Applications With JavaShlomo Swidler
Challenges faced by developers of cloud-computing applications and Java-based solutions. Including an overview of Google App Engine, Amazon Web Services, and sample Java code demonstrating design patterns that will scale in the cloud.
This document provides information about a 30 Days of Google Cloud program being run by GDSC and RobSoc at Miranda House, University of Delhi. The summary includes:
- The program aims to help participants unlock benefits and gain hands-on experience in Google Cloud over 30 days by completing skill badges and tracks in cloud engineering and data science/machine learning.
- Participants can choose to complete one track for rewards, or both tracks for additional rewards, including a certificate of appreciation from Google and goodies.
- The program will provide training to help participants earn skill badges by completing hands-on labs and assessments to demonstrate their cloud skills.
Delivered @ MusicCityCode 6/2/2017
Knowledge is power, but is it if you're not using it? What if the application you delivered to your customers was extremely intelligent? It could retrieve, analyze and use the massive amounts of data that businesses are generating at an astronomical rate.
It could analyze business deals, predict potential issues, proactively recommend business decisions and estimate profit, loss and risks.
Those things provide direct benefits to your company. Churning through that data by hand doesn't. Enter Azure Machine Learning.
In this session you will learn how to integrate Azure Machine Learning into your existing applications and workflows with REST services. You will learn how to deliver a modular, maintainable solution to your customers that allows them to analyze their data.
You will learn to:
* Numerous ways to abstract business rules, workflows, AI (Machine Learning) and more into your applications
* How to Integrate Azure Machine Learning into your existing Applications and Processes
* Create Azure Machine Learning Experiments
* Retrieve the Score from an Azure Machine Learning Experiment and integrate it into your applications and processes
* Integrate numerous Machine Learning Experiments from the Azure Machine Learning Marketplace into your existing applications and processes
* Learn various concepts for abstracting and managing services and api's.
The document provides a 12-step roadmap for becoming a data engineer, including recommended courses, books, and hands-on projects for skills like computer science fundamentals, programming with Python and SQL, Linux, big data systems, data warehousing, batch and stream processing, cloud computing, data orchestration with Airflow, and data engineering management. It also shares additional learning resources like blogs, podcasts, conferences, YouTube channels, and people to follow on social media to continue expanding data engineering knowledge.
Karshil Sheth is a computer science student from Indus University in Ahmedabad, India with experience in web development, Java, and databases. He has worked as an intern at multiple companies developing websites, applications, and databases using technologies like Java, PHP, HTML, CSS, and MySQL. He is skilled in languages like Java, Python, C++, and databases like MySQL, Oracle, and has certifications in Java and training in technologies like C, C++, Python, and Hadoop.
This document outlines the syllabus for an Advanced Computer Networks course. It includes the following key points:
1. The course is taught by Dr. S. Sridevi and covers milestones in conventional networking, software defined networking (SDN), and applications of artificial intelligence and machine learning algorithms to network management, security, and data analysis.
2. The pre-requisite for the course is an Introduction to Computer Networks course.
3. The course outcomes are for students to understand conventional and SDN, implement SDNs using Mininet and Raspberry Pi, and understand network management and security using AI/ML algorithms.
GCSJ 2023 is a fantastic opportunity to immerse yourself in Google Cloud technologies ☁️. Whether you're a beginner or an experienced cloud practitioner, this session will be a stepping stone to enter the world of cloud computing.
This document provides information about courses for a Bachelor of Technology in Computer Science and Engineering for Semester VIII. It lists 5 required courses covering topics like project work, electives in professional and open electives, and corresponding labs. Details are provided for each course including credit hours, examination scheme, topics covered and suggested reading materials. The document also outlines the eligibility criteria for elective courses.
This document provides information about the Google Developer Student Club (GDSC) at the Faculty of Engineering and Technology, Jain University. It introduces the community leaders and faculty advisor. It summarizes the accomplishments of GDSC in the previous year. It then describes the benefits of joining GDSC such as learning skills, accessing Google resources, networking opportunities, and completing milestones to earn schwags.
The document outlines the 30 Days of Google Cloud program that GDSC will run, including the two tracks of Cloud Engineering and Data Science & Machine Learning. It lists the topics that will be covered in each track and the timeline for student registration, the campaign, and rewards distribution. Completing one track earns participants
The document discusses how cloud computing can transform military training and education. It begins by defining cloud computing and describing its key attributes such as scalability, reliability, and low cost. It then outlines how the cloud could benefit the enterprise through cost-effective infrastructure, empower instructors to create and share content, and tailor training to individual trainees' careers. The implications of cloud delivery and analytics are examined, including cloud gaming and simulation as well as using big data and machine learning to analyze training outcomes. Finally, the document argues that organizations should develop a cloud strategy to unify isolated training systems and take advantage of the cloud's potential to streamline infrastructure and make training more data-driven.
End To End Machine Learning With Google Cloud Tu Pham
This document discusses end-to-end machine learning with Google Cloud. It outlines an 8-step process for collecting raw data, converting it to Apache Parquet files, uploading it to Cloud Storage, exploring it in Datalab, developing models in TensorFlow/Scikit-learn, training models at scale on Cloud ML Engine, deploying models via APIs on Compute Engine, and exposing APIs with Load Balancing. Key principles discussed are keeping it simple, avoiding repetition, and focusing on scalability, performance, and cost optimization. The presenter encourages planning systems with single responsibilities, separating real-time and batch flows, and saving on networking, instance, and storage costs through monitoring.
The document outlines a 90-hour summer training course on Internet of Things (IoT) with real-time application projects. The training will take place in June 2018 in Faridabad, India and cover 11 modules, including introductions to IoT, sensor technologies, programming with Python, cloud computing models, IoT security issues, and industrial IoT systems. Hands-on sessions will focus on interfacing sensors like temperature, humidity, and ultrasonic range finders with Raspberry Pi kits and developing IoT projects around environmental monitoring, security, and home automation. The schedule provides duration and learning objectives for each module.
This course introduces students to cloud computing, artificial intelligence, and decentralized applications technologies. Students will learn about major cloud platforms and related services for computing, storage, networking, big data, and machine learning. They will combine these services to create intelligent autonomous networked solutions. The course also covers decentralized computing using Ethereum, smart contracts, and developing decentralized applications. Students will build their own projects combining cloud and decentralized technologies.
This document provides an overview of IBM's cloud platforms and services for developing applications. It discusses IBM Bluemix as a Platform as a Service (PaaS) that allows deploying apps quickly using managed infrastructure. Bluemix embraces Cloud Foundry and provides over 160 services for building apps. The IBM IoT Foundation is also summarized as connecting devices to send data to the cloud and build apps accessing that device data through APIs. The document promotes signing up for a free Bluemix trial and finding open datasets and APIs to use for app development.
A Strategic Approach: GenAI in EducationPeter 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.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
Thinking of getting a dog? Be aware that breeds like Pit Bulls, Rottweilers, and German Shepherds can be loyal and dangerous. Proper training and socialization are crucial to preventing aggressive behaviors. Ensure safety by understanding their needs and always supervising interactions. Stay safe, and enjoy your furry friends!
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
2. Index
Web development
Android development
Game development
Cloud computing
Cyber security
Data science & ML
Data structure
Programming languages
Learning resources from tech giants
Official Online learning platforms
Platform for programmers
Student programs
3. Web development
1. complete web development in written form Learn
web development | MDN (mozilla.org)
2. MIT open Courseware
Software Engineering for Web Applications | Electrical Engineering and Computer Science |
MIT OpenCourseWare
3. khan academy
Computer programming | Computing | Khan Academy
4. Complete web development from Udemy
The Complete 2021 Web Development Bootcamp | Udemy
The Web Developer Bootcamp: Learn HTML, CSS, Node, and More! | Udemy
5. Udacity
Become a Full Stack Web Developer (udacity.com)
6. Coursera
Full-Stack Web Development with React | Coursera
7. Edx.org
Full Stack Cloud Developer Professional Certificate | edX
8. Complete web development from YouTube
Web Development Tutorials For Beginners In Hindi: HTML, CSS, JavaScript & More - YouTube
Web Development Course - YouTube
4. android development
1. Google
Training Courses | Android Developers
2. Flutter
https://flutter.dev/docs/deployment/android
3. Udemy
The Complete Android Oreo Developer Course - Build 23 Apps! | Udemy
4. udacity
Android Kotlin Developer Online Course (udacity.com)
5. coursera
Android App Development | Coursera
Best software for UI/UX design
Adobe XD | Fast & Powerful UI/UX Design & Collaboration Tool
Bootstrap Studio - The Revolutionary Web Design Tool
5. Game development
1. geek for seeks
How to Get Started with Game Development? - GeeksforGeeks
2. unity
Learn game development w/ Unity | Courses & tutorials in
game design, VR, AR, & Real-time3D | Unity Learn
3. Amazon
Game Tech - Digital Training | AWS (amazon.com)
4. udemy
2D: C# Unity Developer 2D Coding: Learn to Code Video Games | Udemy
3D: Video Game Development Using Unity: Code Games with C# | Udemy
5. Coursera
Game Design and Development with Unity 2020 | Coursera
6. Edx.org
Computer Science for Game Development Professional Certificate | edX
7. youtube
Game Development Course - YouTube
6. Cloud computing
1. IBM
Get started with cloud computing – IBM Developer And
Introduction to Cloud | Free Courses in Data Science, AI, Cloud Computing, Containers,
Kubernetes, Blockchain and more. (cognitiveclass.ai)
2. google
Google Cloud Computing Foundations: Cloud Computing Fundamentals | Qwiklabs
3. Microsoft
Foundations of cloud computing for developers - Learn | Microsoft Docs
4. Amazon
AWS Cloud Practitioner Essentials | AWS Training & Certification
5. Udemy
Introduction to Cloud Computing on Amazon AWS for Beginners | Udemy
6. Udacity
Become an AWS Cloud Developer (udacity.com)
7. Edx.org
Cloud Computing MicroMasters® Program | edX
8. Coursera
Cloud Computing | Coursera
9. NPTEL
NPTEL :: Computer Science and Engineering - NOC:Cloud computing
<<<<<pathway>>>>>
Learn Cloud Computing from scratch (cloudacademy.com)
7. Cyber security
1. IBM
Cybersecurity Training and Courses - IBM Skills
And
Apply end to end security to a cloud application | Free Courses in Data Science, AI, Cloud
Computing, Containers, Kubernetes, Blockchain and more. (cognitiveclass.ai)
2. google
Networking & Security Courses | Google Cloud Training
3. Amazon
Security - Digital and Classroom Training | AWS (amazon.com)
4. Udacity
Training for cybersecurity with Udacity
5. Simple learn
Cyber Security Tutorial: A Step-by-Step Tutorial [Updated 2021] (simplilearn.com)
6. NPTEL
Vol 1: NPTEL :: Computer Science and Engineering - NOC:Introduction to Information Security 1
Vol 2: NPTEL :: Computer Science and Engineering - NOC:Information Security - 2
Vol 3 NPTEL :: Computer Science and Engineering - NOC:Information Security-3
Vol 4: NPTEL :: Computer Science and Engineering - NOC:Information security - 4
Vol 5: NPTEL :: Computer Science and Engineering - NOC:Information Security - 5
7. Udemy
Vol1: The Complete Cyber Security Course : Hackers Exposed! | Udemy
Vol2: Complete Cyber Security Course: Class in Network Security | Udemy
Vol3: The Complete Cyber Security Course : Anonymous Browsing! | Udemy
Vol4:The Complete Cyber Security Course : End Point Protection! | Udemy
8. Coursera
Cybersecurity | Coursera
9. Edx.org
Cybersecurity MicroMasters® Program | edX
8. Data science
1. IBM
IBM Learning Journeys - IBM Training - Global And
Vol:1Data Science Fundamentals | Free Courses in Data Science, AI, Cloud Computing, Containers,
Kubernetes, Blockchain and more. (cognitiveclass.ai)
Vol:2Data Science with Python | Free Courses in Data Science, AI, Cloud Computing, Containers,
Kubernetes, Blockchain and more. (cognitiveclass.ai)
2. Amazon
Data Scientist - Learning Path | AWS (amazon.com)
3. Google
Data Science on Google Cloud: Machine Learning | Qwiklabs And
Data science and machine learning on Cloud AI Platform (google.com)
4. Microsoft
Data Scientist - Learn | Microsoft Docs
5. udemy
Data Science Training Course: Data Scientist Bootcamp | Udemy
6. udacity
Data Science Online Courses & Programs (udacity.com)
7. coursera
IBM Data Science Professional Certificate | Coursera
8. Edx.org
HarvardX Data Science Professional Certificate | edX
9. NPTEL
NPTEL :: Computer Science and Engineering - NOC:Python for Data Science
R:1NPTEL :: Mathematics - NOC:Essentials of Data Science With R Software _ 1: Probability
and Statistical Inference
R:2NPTEL :: Mathematics - NOC:Essentials of Data Science With R Software _ 2: Sampling
Theory and Linear Regression Analysis
10. upgrad certified programme
Executive PG Programme in Data Science | upGrad & IIITB
9. Machine learning
1. IBM
What is Machine Learning? - India | IBM
And
Machine Learning with Python | Free Courses in Data Science, AI, Cloud Computing,
Containers, Kubernetes, Blockchain and more. (cognitiveclass.ai)
2. Google
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud | Qwiklabs And
Tutorials | TensorFlow Core
3. Microsoft
1:Microsoft Certified: Azure AI Fundamentals - Learn | Microsoft Docs
2: Microsoft Certified: Azure AI Engineer Associate - Learn | Microsoft Docs
4. Amazon
Machine Learning (ML) - Digital and Classroom Training | AWS (amazon.com)
5. Coursera
Machine Learning by Stanford University | Coursera
6. Udemy
Machine Learning A-Z (Python & R in Data Science Course) | Udemy
7. Udacity
Become a Machine Learning Engineer (udacity.com)
8. Edx.org
Machine Learning and Finance Professional Certificate | edX
9. NPTEL
NPTEL :: Computer Science and Engineering - NOC:Machine Learning,ML
10. MIT
Machine Learning | Electrical Engineering and Computer Science | MIT OpenCourseWare
11. Stanford
Stanford Engineering Everywhere | CS229 - Machine Learning
<<<<pathway>>>>
A Learning Path To Becoming a Data Scientist | by Sara A. Metwalli | Towards Data Science
10. Data structures
1. GeekForSeek
Course | 11 Weeks Workshop on Data Structures and Algorithms (geeksforgeeks.org) and
Course | Data Structures and Algorithms (geeksforgeeks.org)
2. Codechef
Learn Data Structures and Algorithms | CodeChef
3. Coursera
Data Structures and Algorithms | Coursera
4. Edx.org
Data Structures and Algorithms Professional Certificate | edX
5. Udemy
Mastering Data Structures and Algorithms with C and C++ Training | Udemy
6. Udacity
Learn Data Structures and Algorithms (udacity.com)
7. NPTEL
NPTEL :: Computer Science and Engineering - Data Structures And Algorithms
8. MIT
Advanced Data Structures | Electrical Engineering and Computer Science | MIT
OpenCourseWare
9. Youtube
C++ Full Course | C++ Tutorial | Data Structures & Algorithms - YouTube
11. Programming languages
C++
Learncpp
The C++ Tutorial | Learn C++ (learncpp.com) Udemy
Learn C++ Programming -Beginner to Advance- Deep Dive in C++ | Udemy
Udacity
Learn C++ Online (udacity.com)
Coursera
С/C++ for competitive programming | Coursera
Edx
Programming & Data Structures MicroBachelors® Program | edX
Nptel
NPTEL :: Computer Science and Engineering - NOC:Programming in C++
MIT
Effective Programming in C and C++ | Electrical Engineering and Computer Science | MIT
OpenCourseWare
YouTube
C++ Full Course | C++ Tutorial | Data Structures & Algorithms - YouTube
13. Python
Learnpython
Learn Python - Free Interactive Python Tutorial
Udemy
Python Bootcamps: Learn Python Programming and Code Training | Udemy
Udacity
Intermediate Python Online Nanodegree Course (udacity.com)
Coursera
Python 3 Programming | Coursera
Edx.org
Computational Thinking using Python XSeries Program | edX
NPTEL
NPTEL :: Physics - NOC:Computational Science and Engineering Using Python
Youtube
Python Tutorials For Absolute Beginners In Hindi - YouTube
14. Learning Platforms by tech companies
1. Amazon-
Training and Certification | Cloud Skills Courses and Programs | AWS (amazon.com)
1. Google:-
Learn online marketing with free courses - Google Digital Garage
(learndigital.withgoogle.com)
And
Learning experience | Google Developers
And
Qwiklabs - Hands-On Cloud Training
2. Microsoft :-
Microsoft Learn | Microsoft Docs
3. IBM:-
Data Science and Cognitive Computing Courses - Cognitive Class | Free Courses in Data
Science, AI, Cloud Computing, Containers, Kubernetes, Blockchain and more. And
Open P-TECH (ibm.com)
And
IBM Training
4. Adobe:-
Learn Graphic Design: Graphic Design How Tos | Adobe
15. Online mooc platforms
1. Coursera:-
Coursera | Online Courses & Credentials From Top Educators. Join for Free
2. Edx.org:- edX | Free Online Courses by Harvard,
MIT, & more | edX
3. Udemy:-
Online Courses - Anytime, Anywhere | Udemy
4. Udacity:-
Learn the Latest Tech Skills; Advance Your Career | Udacity
5. NPTEL:-
Nptel, online courses and certification, Learn for free
6. MIT open courseware
OCW Course Index | MIT OpenCourseWare | Free Online Course Materials
7. Stanford
Stanford Engineering Everywhere | Home
8. Khan academy
Khan Academy | Free Online Courses, Lessons & Practice
16. <<<<platforms for programmers>>>>
1. GitHub
2. Topcoder Top Technology Talent On-Demand
3. Kaggle: Your Machine Learning and Data Science Community
4. CodeChef
5. Codeforces
6. GeeksforGeeks
7. Coding Ninjas
8. HackerRank
<<<jobs & internship>>>
9. Internships | Summer Internship 2021 (internshala.com)
10. Internship.co.in - India's No 1 Internship Site
11. Hire Freelancers & Find Freelance Jobs Online | Freelancer
17. Student communities & programs
1. Microsoft Learn Student Ambassadors
2. Google Developer Groups (community.dev)
3. GitHub Student Developer Pack - GitHub Education
4. IBM Z Global Student Hub - Group home - IBM Z
Popular campagions
1. TCS CodeVita: Online Programming Competition to Connect Students
2. Google’s Coding Competitions - Code Jam, Hash Code and Kick Start
3. Home | Google Summer of Code
4. Student Developer Competitions | Imagine Cup (microsoft.com)
5. Facebook Coding Competitions