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Big Data Courses

186 Courses

California Institute of Technology Udemy

SAP Big Data Predictive Analytics : An Overview

Embark on a journey to future-proof your career with the comprehensive 'SAP Big Data Predictive Analytics: An Overview' course on Udemy. Dive into the world of big data, mastering concepts in business intelligence, predictive analytics, and data science. This course covers essential topics such as data mining, data warehousing, and statistical.
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California Institute of Technology Udemy

How To Build Unicorn Tech Startups with Sramana Mitra

Join the transformative course "How To Build Unicorn Tech Startups with Sramana Mitra" available on Udemy. Dive into the world of billion-dollar tech unicorns by exploring detailed case studies and gaining hard-won advice from successful founders. This course sheds light on innovative business models and the journey of tech startups achieving.
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California Institute of Technology Udemy

Getting Started with Data Management

Embark on your journey to mastering data management with our comprehensive course, 'Getting Started with Data Management,' offered by Udemy. This course is tailored to help you understand how organizations manage their data effectively. Gain foundational knowledge in data analysis using industry-standard tools like Python and SQL. Unlock the p.
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California Institute of Technology Udemy

Complete PySpark & Google Colab Primer For Data Science

Master the art of building machine learning and neural network models using PySpark and Google Colab with this comprehensive primer. Perfectly suited for aspiring data scientists, this Udemy course covers essential topics including machine learning, big data, deep learning, and more. Discover how to efficiently process data and perform stati.
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California Institute of Technology Udemy

Intro to Big Data & Decisions in Healthcare , Plain & Simple

Discover how to navigate the complexities of big data in the healthcare sector with the introductory course, "Intro to Big Data & Decisions in Healthcare, Plain & Simple," offered by Udemy. This course is designed to equip you with the knowledge to effectively manage and utilize big data, enhancing your ability to make informed clinical decisio.
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California Institute of Technology Udemy

Linear Algebra for Data Science & Machine Learning A-Z 2023

Event Title: Linear Algebra for Data Science & Machine, Learning A-Z 2023 Description: Dive into the essentials of Linear Algebra tailored specifically for Data Science, Big Data, Machine Learning, Engineering, and Computer Science. This comprehensive course on Udemy is designed to help you master the core concepts and techniques of Linear Algebra,.
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provider Udemy
pricing Paid Course
duration 18 hours
sessions On-Demand

Becoming a Big Data Analyst: A Step-by-Step

Big data analysis is a relatively new, but quite in-demand area of the labour market. The demand for data scientists is constantly growing. Big Data are data sets of very large size, which are also characterised by diversity and high update rate. A big data analyst is a specialist who identifies and investigates patterns in data using special software tools.

Overview of Big Data and AI

The generation and sharing of big data across devices is happening in almost every social sphere. Big Data is used by giants such as Google, Uber, IBM, Amazon to optimise customer experience, reduce the risk of fraud and data security threats. Big Data specialists after big data and ai courses are needed in: marketing, search technology, retail, social media, gaming, personalisation, speech technology, financial institutions and recommendation systems.

Skills You Will Gain

It is not necessary for an analyst to have a university degree in information technology. However, a Data Analyst must understand business processes, understand statistics, perform machine learning, and be able to work with tools.

Types of data analysis:

The duties of the analyst also include tasks on Business Inteligence (BI) and optimisation of processes in production. A specialist should know the methods of analysing business processes: SWOT, ABC, IDEF, BPMN, MTP, PDCA, EPC and others.

Basic Data Analyst skills:

Additionally, the analyst may use Apache Storm, Apache Kinesis, Apache Spark Streaming.

Big Data specialists need to be able to build graphical models using Bayesian and neural networks, clustering and types of analysis. A Data Scientist, Data Analyst or Data Engineer should be skilled in working with Data Lakes, as well as security and Data Governance. Becoming an expert will help you develop each of these skills in depth.

Why Learn Big Data and AI?

In the era of digital transformation, when the amount of data doubles every two years, the art of analysing and using it has become not just an important skill but also a key competitive advantage. In the different fields, traditionally based on knowledge and experience, big data and machine learning course opens new horizons. With the ability to analyse data in depth, we have a tool that allows us to not only respond to current educational needs, but also to predict them, adapting to changing realities faster than ever before.

Career Opportunities and Job Roles

Let's take a look at the main roles and vacancies in Big Data and Data Science.

Data Scientist

A Data Scientist is a specialist who analyses data and develops machine learning with big data to solve business problems. Key responsibilities include:

The Data Scientist should have a strong knowledge of statistics, programming and machine learning.

Data Engineer

The Data Engineer is responsible for building and maintaining the infrastructure for data processing. Key responsibilities include:

The Data Engineer plays a key role in ensuring that data is available and ready for analysis.

Big Data Engineer

The Big Data Engineer develops and maintains systems to process large amounts of data. Key responsibilities include:

The Big Data Engineer should have in-depth knowledge of distributed computing and big data.

Machine Learning Engineer

Machine Learning Engineer specialises in the design and implementation of machine learning models. Key responsibilities include:

The Machine Learning Engineer must have a strong knowledge of machine learning and programming.

Industry Demand

Big Data and AI are two rapidly developing fields that play a key role in today's world. Big Data refers to processing and analysing huge amounts of data that cannot be processed using traditional methods. Data Science, on the other hand, involves the use of statistical methods, machine learning and other technologies to extract knowledge and insights from data. These fields are of great importance to business, science and technology as they enable better informed decision-making and the development of innovative products and services!