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Data Science & Artificial Intelligence Demand in the UK

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The United Kingdom has more than earned its sterling reputation as a powerhouse of technological excellence. It is the go-to location for expert knowledge, inventive application, and faultless execution. Whether it's artificial intelligence, blockchain, cyber security, or data analytics, the UK is at the forefront of some of the world's most intriguing technological breakthroughs. Best-in-class tech firms require the best-in-class tech personnel. The UK workforce has a multitude of talents, whether it's access to professionals in AI, IoT, or cyber security: there are 240,000 digital technology employees in London alone.


Is Data Science and Artificial Intelligence in Demand in UAE

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With a GDP of AED 1.5 trillion in 2020, the UAE's economy is the fifth-largest in the Middle East. The UAE economy, which was once reliant on oil exports, is now increasingly dependent on earnings from petroleum and natural gas. Economic diversification has occurred in recent years, particularly in Dubai. According to studies, the worldwide number of internet-connected devices is predicted to reach 1 trillion by 2030, with the UAE alone expected to achieve this amount by 2050. As a transit country between the East and the West with a pro-business environment, the UAE has become a technology powerhouse for the Internet of Things in all fields, enabling digital transformation in airports, freight, and logistics.


Top Resources To Learn Feature Engineering

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Data analysing, irrespective of its form, can be extremely chaotic and challenging. This is where feature engineering steps in. A method to ease data analysis, feature engineering simplifies data reading for machine learning models. A feature or variable is nothing but the numerical representation of all kinds of data– structured and unstructured. Feature engineering is a vital part of the process of predictive modelling.


Why You Should Learn Data Science?

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Data Science is a bona-fide field conjoining domain expertise, programming skills, and knowledge of mathematics and statistics to extricate useful insights from data. Well, there's no doubt that this specific technology has grabbed a lot of attention, and if you still want to know What Is Data Science? Yes, by enrolling in its professional course, you will get proper in-depth information concerning its section. You will learn about deep neural networks, execute linear and logistic regressions in Python, imply your skills to real-life business cases, etc.


Artificial Intelligence Tutorial for Beginners

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This Artificial Intelligence tutorial provides basic and intermediate information on concepts of Artificial Intelligence. It is designed to help students and working professionals who are complete beginners. In this tutorial, our focus will be on artificial intelligence, if you wish to learn more about machine learning, you can check out this tutorial for complete beginners tutorial of Machine Learning. Through the course of this Artificial Intelligence tutorial, we will look at various concepts such as the meaning of artificial intelligence, the levels of AI, why AI is important, it's various applications, the future of artificial intelligence, and more. Usually, to work in the field of AI, you need to have a lot of experience. Thus, we will also discuss the various job profiles which are associated with artificial intelligence and will eventually help you to attain relevant experience. You don't need to be from a specific background before joining the field of AI as it is possible to learn and attain the skills needed. While the terms Data Science, Artificial Intelligence (AI) and Machine learning fall in the same domain and are connected, they have their specific applications and meaning. Simply put, artificial intelligence aims at enabling machines to execute reasoning by replicating human intelligence. Since the main objective of AI processes is to teach machines from experience, feeding the right information and self-correction is crucial. The answer to this question would depend on who you ask. A layman, with a fleeting understanding of technology, would link it to robots. If you ask about artificial intelligence to an AI researcher, (s)he would say that it's a set of algorithms that can produce results without having to be explicitly instructed to do so. Both of these answers are right.


Data Science Tutorials - AI Summary

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Deep Dive into the World of Data Science Through this Blog, we will read about what is data science, why it is such a buzzword these days, what makes data science such an effective and a hot technology to look forward to, what is it like to be a data scientist, what do you need to achieve to be a data scientist. You will also be made familiar about the applications, advantages, disadvantages, examples, real-life use cases, differences between machine learning and artificial intelligence vs neural networks vs deep learning vs prediction analysis. We will also be reading about the various frameworks and libraries which are in very popular demand these days such as Numpy which stands for numerical python, Pandas for data frames, Scikit learn for cross-validation techniques and other model fitting techniques, seaborn for analysis, heatmaps, Tensorflow, etc. Data science is probably the most unexplored territory today and the scope to learn and create and do something out of the box is way too much in this technology and field of sciences and mathematics. Through this Blog, we will read about what is data science, why it is such a buzzword these days, what makes data science such an effective and a hot technology to look forward to, what is it like to be a data scientist, what do you need to achieve to be a data scientist. You will also be made familiar about the applications, advantages, disadvantages, examples, real-life use cases, differences between machine learning and artificial intelligence vs neural networks vs deep learning vs prediction analysis.


Data Science Tutorials

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Through this Blog, we will read about what is data science, why it is such a buzzword these days, what makes data science such an effective and a hot technology to look forward to, what is it like to be a data scientist, what do you need to achieve to be a data scientist. You will also be made familiar about the applications, advantages, disadvantages, examples, real-life use cases, differences between machine learning and artificial intelligence vs neural networks vs deep learning vs prediction analysis. We will also be reading about the various frameworks and libraries which are in very popular demand these days such as Numpy which stands for numerical python, Pandas for data frames, Scikit learn for cross-validation techniques and other model fitting techniques, seaborn for analysis, heatmaps, Tensorflow, etc. Data science is probably the most unexplored territory today and the scope to learn and create and do something out of the box is way too much in this technology and field of sciences and mathematics.


Build Spark Machine Learning and Analytics (5 Projects)

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And learn to use it with one of the most popular way! One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Superset! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Apache Superset to solve their big data problems! What is this course about? This course covers all the fundamentals about Apache Spark Machine Learning Project with Scala and teaches you everything you need to know about developing Spark Machine Learning applications using Scala, the Machine Learning Library API for Spark.


Data Analysis with Python

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Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more! Topics covered: 1) Importing Datasets 2) Cleaning the Data 3) Data frame manipulation 4) Summarizing the Data 5) Building machine learning Regression models 6) Building data pipelines Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts: Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets.


Practice Test to prepare for Apache Spark Certification - Databricks Certification exam. - Projects Based Learning

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Databricks is founded by the creators of Apache Spark, Databricks combines the best of data warehouses and data lakes into a lakehouse architecture. Databricks is an American enterprise software company founded by the creators of Apache Spark. The company has also created Delta Lake, MLflow and Koalas, open source projects that span data engineering, data science and machine learning. Databricks develops a web-based platform for working with Spark, that provides automated cluster management and IPython-style notebooks. Gartner has classified Databricks as a leader in the last quadrant for Data Science and Machine Learning platforms.