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This Power BI course is a hands-on, project-based learning experience tailored for learners at all levels, from beginners to advanced users. The course focuses on building a complete dashboard report for an e-learning company, guiding you through the entire process of data extraction, transformation, and loading (ETL) within Power BI.Throughout this course, you will learn how to:Clean and prepare data: Learn how to clean raw datasets and merge them effectively, ensuring data quality and consistency.Data Modeling: Build relationships between different datasets and create meaningful data models to drive accurate analysis.Dashboard Design: Use Power BI’s intuitive tools to create stunning, interactive dashboards that present key insights clearly.Pagination in Dashboards: Add professional touches by implementing pagination features in reports to enhance navigation and readability.By the end of this course, you will have built a comprehensive Power BI dashboard from scratch, enabling you to apply these skills in real-world e-learning or business analytics scenarios.Material IncludesSample datasets for practice (related to the e-learning company project)Step-by-step video tutorialsPower BI Dashboard templatesAccess to the course discussion forum for peer supportCertificate of completionWhat Will You Learn?Overview of Power BI and its componentsData Extraction, Transformation, and Loading (ETL)Importing datasets from various sources (Excel, databases, etc.)Cleaning and transforming raw data for analysisMerging multiple datasets for comprehensive insightsC

Within the area of Computer Vision is the sub-area of Optical Character Recognition (OCR), which aims to transform images into texts. OCR can be described as converting images containing typed, handwritten or printed text into characters that a machine can understand. It is possible to convert scanned or photographed documents into texts that can be edited in any tool, such as the Microsoft Word. A common application is automatic form reading, in which you can send a photo of your credit card or your driver's license, and the system can read all your data without the need to type them manually. A self-driving car can use OCR to read traffic signs and a parking lot can guarantee access by reading the license plate of the cars!To take you to this area, in this course you will learn in practice how to use OCR libraries to recognize text in images and videos, all the code implemented step by step using the Python programming language! We are going to use Google Colab, so you do not have to worry about installing libraries on your machine, as everything will be developed online using Google's GPUs! You will also learn how to build your own OCR from scratch using Deep Learning and Convolutional Neural Networks! Below you can check the main topics of the course:Recognition of texts in images and videos using Tesseract, EasyOCR and EASTSearch for specific terms in images using regular expressionsTechniques for improving image quality, such as: thresholding, color inversion, grayscale, resizing, noise removal, morphological operations and perspective transformationEAST architecture and EasyOCR library for better performance in natural scenesTraining an OCR from scratch using TensorFlow and modern Deep Learning techniques, such as Convolutional Neural NetworksApplication of natural language processing techniques in the texts extracted by OCR (word cloud and named entity recognition)

Did you struggle to understand Prototypes, the Prototype Chain, or Classes in JavaScript? Do concepts like inheritance, function constructors, and object instantiation seem confusing?Then this course is for you!In this hands-on course, you will deeply explore Object-Oriented Programming (OOP) in JavaScript, gaining the skills to write cleaner, more structured, and reusable code. Understanding how JavaScript handles objects, inheritance, and encapsulation is essential for becoming a proficient JavaScript developer.What You Will Learn:• What is a Prototype? – Understand how JavaScript handles objects under the hood.• How the Prototype Chain works – Learn how properties and methods are inherited.• Creating and using Function Constructors – Master an older but essential way to create objects.• Using Object.create() – Learn how to create objects without function constructors.• How to inherit properties and methods – Implement inheritance correctly in JavaScript.• Creating instances of specific prototypes – Learn how instances are linked to their prototype.• The difference between classical and prototypal inheritance – Understand why JavaScript is different from languages like Java or C++.• ES6 Classes and how they work internally – Uncover the modern approach to OOP in JavaScript.• Super() and Extends – Learn how to create class hierarchies with ease.• Encapsulation and private fields – Secure your data and improve code maintainability.This course is practical and beginner-friendly, meaning you won’t just learn theory—you wil

HTML CSS and JavaScript Project For BeginnersHey everybody, I hope you are all fine, today I'm going to share with you the complete course for absolute beginners, who want to improve their logic and skills in HTML CSS, and also JavaScript. I designed the HTML CSS and JavaScript Projects-based course for you, so you can learn everything from scratch.In the vast realm of web development, embarking on the journey of creating your very first website is an exciting and rewarding experience. As a beginner, it's crucial to grasp the fundamentals of web technologies, and three pillars stand out prominently: HTML, CSS, and JavaScript. In this article, we will walk you through the process of building simple yet functional-based projects, providing insights into these essential technologies and empowering you to create your own digital masterpiece.HTML is the backbone of any web page, shaping its structure and content. At its core, HTML uses tags to encapsulate different elements, giving browsers the necessary information to display a page accurately.CSS comes into play when you want to style and beautify your HTML elements, enhancing the visual appeal of your website. As you delve into CSS, you'll encounter selectors, properties, and values that enable you to control the layout, colors, and fonts of your webpage.Selectors allow you to target specific HTML elements, while properties dictate their appearance. Understanding the box model is essential, as it governs how elements are rendered in terms of width, height, padding, margin, and border. Grasping CSS concepts will help you transform a plain HTML structure into an aesthetically pleasing web page.JavaScript brings life to your static web pages by adding interactivity and dynamic behavior. As a scripting language, it runs on the client side, allowing you to manipulate the Document Object Model (DOM) – the structured representation of your HTML document

In this course, we will dive into the world of Natural Language Processing. We will demonstrate how Deep Learning has re-shaped this area of Artificial Intelligence using concepts like word vectors and embeddings, strucutured deep learning, collaborative filtering, recurrent neural networks, sequence-to-sequence models and transformer networks. In our journey, we will be mostly concerned with how to represent the language tokens, being at the word or character level, and and how to represent their aggregation, like sentences or documents, in a semantically sound way. We start the journey by going through the traditional pipeline of text pre-processing and the different text features like binary and TF-IDF features with the Bag-of-Words model. Then we will dive into the concepts of word vectors and embeddings as a general deep learning concept, with detailed discussion of famous word embedding techniques like word2vec, GloVe, Fasttext and ELMo. This will enable us to divert into recommender systems, using collaborative filtering and twin-tower model as an example of the generic usage of embeddings beyond word representations. In the second part of the course, we will be concerned with sentence and sequence representations. We will tackle the core NLP of Langauge Modeling, at statistical and neural levels, using recurrent models, like LSTM and GRU. In the following part, we tackle sequence-to-sequence models, with the flagship NLP task of Machine Translation, which paves the way to talk about many other tasks under the same design seq2seq pattern, like Question-Answering and Chatbots. We present the core idea idea of Attention mechanisms with recurrent seq2seq, before we generalize it as a generic deep learning concept. This generalization leads to the to the state-of-the art Transformer Network, which revolutionized the world of NLP, using full attention mechanisms. In the final part of the course, we present the ImageNet moment of NLP, where Transfer Learning comes into play together with pre-tr

Greetings, I am so excited to learn that you have started your path to becoming a Data Scientist with my course. Data Scientist is in-demand and most satisfying career, where you will solve the most interesting problems and challenges in the world. Not only, you will earn average salary of over $100,000 p.a., you will also see the impact of your work around your, is not is amazing?This is one of the most comprehensive course on any e-learning platform (including Udemy marketplace) which uses the power of Python to learn exploratory data analysis and machine learning algorithms. You will learn the skills to dive deep into the data and present solid conclusions for decision making. Data Science Bootcamps are costly, in thousands of dollars. However, this course is only a fraction of the cost of any such Bootcamp and includes HD lectures along with detailed code notebooks for every lecture. The course also includes practice exercises on real data for each topic you cover, because the goal is "Learn by Doing"! For your satisfaction, I would like to mention few topics that we will be learning in this course:Basis Python programming for Data ScienceData Types, Comparisons Operators, if, else, elif statement, Loops, List Comprehension, Functions, Lambda Expression, Map and FilterNumPyArrays, built-in methods, array methods and attributes, Indexing, slicing, broadcasting boolean masking, Arithmetic Operations Universal FunctionsPandasPandas Data Structures - Series, DataF