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AI Essentials: Introduction to Artificial Intelligence

AI Essentials: A Simple Introduction to Artificial Intelligence Technologies by MTF Institute

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What you'll learn

• AI, it's Modern History and current Implementations
• Machine Learning
• Neural Networks and Deep Learning
• The relationship between Machine Learning, Neural Networks and Deep Learning
• The theory of Artificial General Intelligence (AGI)
• Intelligent agents
• Natural Language Processing (NLP)
• Computer Vision
• AI Ethics
• AI In Robotics
• Search Algorithms
• Knowledge Representation and Reasoning (KRR)
• Explain-ability and Transparency in AI (XAI)

Description

Welcome to course: AI Essentials: A Simple Introduction to Artificial Intelligence Technologies by MTF Institute

Course provided by MTF Institute of Management, Technology and Finance

MTF is the global educational and research institute with HQ at Lisbon, Portugal, focused on higher & professional hybrid (on-campus and online) education at areas: Business & Administration, Science & Technology, Banking & Finance.

MTF R&D center focused on research activities at areas: Artificial Intelligence, Machine Learning, Data Science, Big Data, WEB3, Blockchain, Cryptocurrency & Digital Assets, Metaverses, Digital Transformation, Fintech, Electronic Commerce, Internet of Things.

MTF is the official partner of: IBM, Intel, Microsoft, member of the Portuguese Chamber of Commerce and Industry, and resident of the incubator "The Fintech House of Portugal".

MTF is present in 205 countries and has been chosen by more than 250,000 students.

Hello everyone, and welcome to my course in Artificial Intelligence (AI)! My name is Mohamed Elfateh, I have been working in the Information Technology field for over a decade. I am interested in learning about modern technologies and sharing my knowledge with others.

What is AI?
AI is a field of computer science that studies how to create machines that can process information, make decisions, and perform specific tasks.

The History of modern AI

The field of artificial intelligence (AI) has a long and rich history, dating back to the early days of computing. However, the field as we know it today was founded in 1956 at a conference at Dartmouth College in New Hampshire. This conference brought together the leading researchers in AI at the time, including Alan Turing, John McCarthy, and Marvin Minsky. The conference is credited with helping to define the field of AI and to set the agenda for future research.

Artificial Intelligence “AI” is a complex field that needs the ability of people from diverse disciplines to work together. As an example, manufacturing autonomous vehicles like self-driving cars requires the work of people from different fields, such as AI Researchers, Automotive Engineers, and Computer Vision Researchers.

AI Researchers develop algorithms that enable self-driving cars to perceive their surroundings, make decisions, and control their movements. Automotive Engineers develop the hardware and software systems that are needed to implement these algorithms, and Computer Vision Researchers develop new techniques for enabling self-driving cars to see and understand the world.

What is Machine Learning?

Machine Learning is a type of Artificial Intelligence (AI) that allows computers to learn from data without explicit programming. In other words, machine learning algorithms can recognize patterns and make predictions based on data, without getting a command. This enables computers to learn new tasks and improve their performance over time without human intervention.

Where is Machine Learning used?

Machine learning is in use by a wide range of applications, including email filtering, Social Media Personalization, Image Recognition, Speech Recognition, fraud detection, Text prediction, Product recommendation, medical diagnosis, Healthcare Personalization, Traffic Prediction.

Neural networks are a type of machine learning algorithm that is inspired by the structure and function of the human brain.

Neural networks can learn complex patterns from data.

Neural networks have been successfully used in areas such as natural language processing.

Deep Learning is a type of machine learning that uses neural networks with multiple layers.

Each layer consists of multiple nodes that can perform diverse tasks. This allows deep learning models to learn more complex patterns from data.

Deep learning has been used to achieve significant results in a wide range of tasks, including image recognition, speech recognition, and machine translation.

Hello Learners, Announcing New Course to You guys !!!!. Most of the courses have Limited Seats so don't get disoppoint, we share daily new opportunites for learning. for get fast notification of courses follow us !!!!

Fastest Laravel app building trick

Automate building Laravel Apis , database migrations and eloquent models and relations , in the oop way of thinking

What you'll learn

• Laravel application building with blueprint
• Automatic building of models and controllers of Laravel using blueprint
• Creating of Events , Jobs , Mailable with linking with the controller very fast
• Building a simple framework to facilitate testing and rebuiling

Description

What you'll learn

• Initialization of a Laravel app using blueprint

• Building blueprint yml file

• Autocreation of database migrations and eloquent models

• Autocreation of Controllers , and actions

• Autocreation of Mailable , Jobs , Events ..

• Change you whole way of thinking of Laravel and Laravel 8 apps building

• Configure your blueprint to work better for you

• Increase development speed

• Promote Laravel conventions

• Just think how your classes and objects should be in the oop way , and tell that to blueprint , and let it be built for you .

• Learn php laravel code generation tool that is so intuitive and straightforward

• Move from your database ERD (entity-relationship diagrams)  to your fully-functioning Data Access Layer.

• Get rid of repetitive tasks and routine debugging process

• Get rid of name-changes headaches by writing the name only once , and leaving the conversion on blueprint

• Focus on the engineering of your new product rather than the implementation itself

• Fast Intro to YML / YAML Syntax

• More and more contents about this topic is to be added , including the extending of several parts of blueprint , to be more great

Reaching a working Laravel api , or Laravel backend is something pretty fast , with blueprint

Even if you have an existing project, blueprint can be adopted and used very efficiently because blueprint engine won't affect any of the existing components , it will only affect components that is created by itself , because blueprint keeps track over every change that it made .

I 've set a simple kit for you so that you can apply your changes and test very fast , so that you can apply your tests in a fast way , and gain more experience on this library , so that your skills in building new apps  with blueprint become dependable .

Maybe you heard about MDA tools that

Sustainable Supply Chain Operations Reference Model - SCOR | Udemy free course

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Sustainable Supply Chain Operations Reference Model - SCOR

SCOR Model Certification: Driving Sustainability in Supply Chain Operations

What you'll learn

• Understand the basics of sustainable supply chain management, its significance, and how it differs from traditional supply chain models.
• Develop the ability to compare and contrast conventional and sustainable supply chains, focusing on their environmental, social, and economic impacts.
• Gain a deep understanding of the different flows in supply chains, including material, information, and finances, and how these can be managed sustainably.
• Gain a deep understanding of the different flows in supply chains, including material, information, and finances, and how these can be managed sustainably.
• Equip yourself with practical skills and strategies to implement sustainable practices in supply chain operations, enhancing both efficiency & sustainability.

Description

Dive into the world of sustainable supply chain management with our comprehensive course, designed to equip you with the knowledge and skills to implement the Supply Chain Operations Reference Model (SCOR) effectively. This course offers a blend of theoretical understanding and practical application, tailored for professionals and students alike who are eager to contribute positively to the environment while maintaining efficient supply chain operations.

The Course Includes:

1. Introduction to Sustainable Supply Chains: We begin with an overview of sustainable supply chain management, exploring its significance in the modern business landscape and the benefits it brings to the environment, society, and economies.

2. Conventional vs. Sustainable Supply Chains: Delve into the differences between traditional and sustainable supply chains, understanding the impacts of each on global sustainability.

3. Understanding Supply Chain Flows: Gain insights into the core flows within supply chains, including products, information, and finances, and how these can be managed sustainably.

4. Mastering SCOR in Sustainable Supply Chains: Learn how to apply the SCOR model to enhance sustainability in various aspects of supply chain management:

   • Sustainable Planning: Strategies for eco-friendly and efficient supply chain planning.

   • Sustainable Sourcing: Best practices for ethical and sustainable sourcing.

   • Sustainable Manufacturing: Approaches for reducing environmental impact in manufacturing processes.

   • Sustainable Logistics: Explore how logistics can be made more sustainable, covering:

     • Eco-Friendly Transportation: Innovative solutions for sustainable transportation.

     • Green Inventory Management: Techniques for managing inventory sustainably.

     • Efficient Warehousing: Strategies for sustainable warehousing practices

   • Sustainable Product Return: Implementing closed-loop supply chains for sustainable product returns.

Through this course, you'll not only acquire a robust understanding of sustainable supply chain concepts but also master practical applications using the SCOR model. Whether you're a supply chain professional, business manager, environmental enthusiast, or student, this course offers valuable insights and skills to make a tangible difference in the world of supply chains.

Zero to Hero NextJS 14 course for real project development complete next js developer in 2023 zero to mastery github next js course free next js projects - 4 nextjs 13 projects (instagram, google) next js 13 course next js advanced course next js roadmap zero to mastery free course best next js course

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Zero to Hero NextJS 14 course for real project development

Learn NextJS 14 and Bootstrap 5 with practical examples after this course you will be ready to build real world projects

What you'll learn

• You will learn to create new next js 14.0 application
• You will learn to use Bootstrap5 and next js 14.0 together
• You will learn about working of Next js app
• You will learn about app router in Next 14.x
• You will learn how to apply animation
• You will learn when to use Server component and when to use Client component
• You will learn how to use Client component and Server components together
• You will learn to develop REST API's in Next JS
• You will also learn to consume REST API in your NEXT JS project
• You will also learn to make calls to other microservices.

Description

In this course you will learn NextJS 14 along with Bootstrap5. You will learn different NextJS concepts like routing, API development, making calls to other microservices, Client side rendering, Server side rendering, combining client side and server side components. You will also learn various techniques of passing data between components and how to use bootstrap and animation. After this course you will ready to work in NextJS 14 in any company and also build any real world project.

Next.js is a powerful and popular open-source React framework that enables developers to build modern and efficient web applications. Launched by Vercel, Next.js simplifies the React development process by providing a robust structure and a range of built-in features.

One of Next.js' key strengths is its support for server-side rendering (SSR) and static site generation (SSG). This means that web pages can be pre-rendered on the server, enhancing performance and search engine optimization. Additionally, Next.js supports client-side rendering, offering flexibility in choosing the rendering method that best suits a project's needs.

The framework's automatic code splitting allows for optimized loading times, ensuring that only the necessary code is sent to the client. With a strong focus on developer experience, Next.js provides a wealth of features, including hot module replacement, automatic routing, and a plugin system for extensibility.

Next.js is well-integrated with the Vercel platform, offering seamless deployment and hosting solutions. Its popularity has grown rapidly within the web development community, thanks to its ease of use, performance benefits, and the ability to handle both small projects and large-scale applications. Whether you're a beginner or an experienced developer, Next.js empowers you to build modern, scalable, and high-performance web applications with ease.

Next.js is a feature-rich React framework that simplifies the development of web applications. Some of its key features include:

1. Server-Side Rendering (SSR): Next.js enables SSR, allowing web pages to be pre-rendered on the server before being sent to the client. This enhances performance and improves search engine optimization.

2. Static Site Generation (SSG): In addition to SSR, Next.js supports SSG, where pages can be generated at build time. This approach is useful for content that doesn't change frequently, resulting in faster page loads.

3. Automatic Code Splitting: Next.js automatically splits code into smaller chunks, sending only the necessary code to the client. This leads to improved loading times and a better user experience, especially on slower networks.

4. Client-Side Rendering (CSR): While SSR and SSG are emphasized, Next.js also supports traditional client-side rendering when needed, offering flexibility in choosing the rendering approach based on specific use cases.

5. Routing: Next.js has automatic route handling based on the file system, making it intuitive for developers. Custom routes can also be configured easily, allowing for more complex application structures.

6. API Routes: Next.js simplifies the creation of API endpoints by providing a straightforward way to build serverless functions within the project. This facilitates seamless communication between the client and server.

7. Hot Module Replacement (HMR): Developers benefit from HMR, which allows for real-time code updates without requiring a full page refresh. This feature speeds up the development process and enhances the developer experience.

8. Middleware Support: Next.js supports middleware, allowing developers to execute custom logic before handling a request. This is particularly useful for tasks like authentication and data fetching.

9. Built-in CSS Support: Next.js provides built-in support for styling with CSS, whether it's traditional CSS, CSS Modules, or popular CSS-in-JS solutions like styled-components.

10. TypeScript Support: Next.js seamlessly integrates with TypeScript, providing static typing for enhanced code quality and developer productivity.

11. Vercel Integration: Next.js is developed by Vercel, and it integrates well with the Vercel platform for deployment and hosting. This combination simplifies the deployment process and offers features like automatic previews and rollbacks.

Data Analyst Skillpath: Excel, SQL & ML with Python in हिंदी | Udemy become a Data Analyst Python Excel, SQL Power BI Data Analyst Course in Hindi free Data analysis using SQL, and Python Python for data analysis in Hindi SQL and Python for data analysis course Data Analyst Tutorial in Hindi Data Analyst course

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Data Analyst Skillpath: Excel, SQL & ML with Python in हिंदी

Learn data analytics by learning Excel, SQL, Python, Analytics & ML concepts from scratch in Hindi

What you'll learn

• Microsoft Excel सीखने वाले सभी नए विद्यार्थियों के लिए कोर्स - इसमें आप Microsoft Excel, Spreadsheets, Formulas, Excel shortcuts, Macros आदि सीखेंगे
• Excel के सबसे ज़रूरी और लोकप्रिय Lookup फंक्शन जैसे - Vlookup, Hlookup, Index और Match फंक्शनों को काफी अच्छे से सीख पाओगे ।
• SQL की सभी ज़रूरी commands को सीख पाओगे |
• Bar chart, Scatter plots, Histogram आदि का उपयोग करके अपने दर्शकों को आकर्षित कर पाओगे ।
• Machine Learning Linear Regression problem के लिए data collection और data preprocessing की गहराई से जानकारी प्राप्त करोगे |

Description

You're looking for a complete course on how to become a data analyst, right?

You've found the right Data Analyst Masterclass with Excel, SQL & Python course! This course will teach you data-driven decision-making, data visualization, data analytics in SQL, and the use of predictive analytics like linear regression in business settings.

After completing this course you will be able to:

• Master Excel's most popular lookup functions such as Vlookup, Hlookup, Index, and Match

• Become proficient in Excel data tools like Sorting, Filtering, Data validations, and Data importing

• Make great presentations using Bar charts, Scatter Plots, Histograms, etc.

• Become proficient in SQL tools like GROUP BY, JOINS, and Subqueries

• Become competent in using sorting and filtering commands in SQL

• Learn how to solve real-life business problems using the Linear Regression technique

• Understand how to interpret the result of the Linear Regression model and translate them into actionable insight

How this course will help you?

A Verifiable Certificate of Completion is presented to all students who undertake this course on Data Analyst Skillpath in Excel, SQL, and Python.

If you are a student, business manager, or business analyst, or an executive who wants to learn Data Analytics concepts and apply data analytics techniques to real-world problems of the business function, this course will give you a solid base for Data Analytics by teaching you the most popular data analysis models and tools

Why should you choose this course?

We believe in teaching by example. This course is no exception. Every Section’s primary focus is to teach you the concepts through how-to examples. Each section has the following components:

• Concepts and use cases of different Statistical tools required for evaluating data analytics models

• Step-by-step instructions on implementing data analytics models

• Downloadable files containing data and solutions used in the course

• Class notes and assignments to revise and practice the concepts

The practical classes where we create the model for each of these strategies are something that differentiates this course from any other course available online.

What makes us qualified to teach you?

The course is taught by Abhishek (MBA - FMS Delhi, B. Tech - IIT Roorkee) and Pukhraj (MBA - IIM Ahmedabad, B. Tech - IIT Roorkee). As managers in the Global Analytics Consulting firm, we have helped businesses solve their business problems using Analytics and we have used our experience to include the practical aspects of business analytics in this course. We have in-hand experience in Business Analysis.

We are also the creators of some of the most popular online courses - with over 1,200,000 enrollments and thousands of 5-star reviews like these ones:

This is very good, i love the fact the all explanation given can be understood by a layman - Joshua

Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy

Our Promise

Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet, or anything related to any topic, you can always post a question in the course or send us a direct message.

Download Practice files, take Quizzes, and complete Assignments

With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts like Data Analytics in MS Excel, SQL, and Python. Each section contains a practice assignment for you to practically implement your learning on Data Analytics.

What is covered in this course?

The analysis of data is not the main crux of analytics. It is the interpretation that helps provide insights after the application of analytical techniques that makes analytics such an important discipline. We have used the most popular analytics software tools which are MS Excel, SQL, and Python. This will aid the students who have no prior coding background to learn and implement Analytics and Machine Learning concepts to actually solve real-world problems of Data Analysis.

Let me give you a brief overview of the course

• Part 1 - Excel for data analytics

In the first section, i.e. Excel for data analytics, we will learn how to use excel for data-related operations such as calculating, transforming, matching, filtering, sorting, and aggregating data.

We will also cover how to use different types of charts to visualize the data and discover hidden data patterns.

• Part 2 - SQL for data analytics

IN the second section, i.e. SQL for data analytics, we will be teaching you everything in SQL that you will need for Data analysis in businesses. We will start with basic data operations like creating a table, retrieving data from a table etc. Later on, we will learn advanced topics like subqueries, Joins, data aggregation, and pattern matching.

• Part 3 - Preprocessing Data for ML models

In this section, you will learn what actions you need to take step by step to get the data and then prepare it for analysis, these steps are very important. We start with understanding the importance of business knowledge then we will see how to do data exploration. We learn how to do univariate analysis and bivariate analysis then we cover topics like outlier treatment, missing value imputation, variable transformation, and correlation.

• Part 4 - Linear regression model for predicting metrics

This section starts with simple linear regression and then covers multiple linear regression.

We have covered the basic theory behind each concept without getting too mathematical about it so that you understand where the concept is coming from and how it is important. But even if you don't understand it, it will be okay as long as you learn how to run and interpret the result as taught in the practical lectures.

I am pretty confident that the course will give you the necessary knowledge on Data Analysis, and the skillsets of a Data Analyst to immediately see practical benefits in your workplace.

Go ahead and click the enroll button, and I'll see you in lesson 1 of this Data Analyst Skillpath course!

Cheers

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