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Big Data Courses

207 Courses

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California Institute of Technology Udemy

Data Science Career Path

Data Science Career Path Elevate your career by mastering the art of Data Science with Udemy’s specialized courses. Dive deep into tackling Big Data challenges and unlock the potential of data-driven decision making. Our comprehensive syllabus spans across: Artificial Intelligence Courses Python Courses Machine Learning.
provider Udemy
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California Institute of Technology LinkedIn Learning

Inside the Mind of an Aspiring Data Scientist

Inside the Mind of an Aspiring Data Scientist Embark on a journey to understand the world of data science with our comprehensive guide. Whether you're just starting out or looking to enhance your skill set, this course offers valuable insights into becoming a data scientist. Explore the potential of a data science career path and find out what c.
provider LinkedIn Learning
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California Institute of Technology LinkedIn Learning

Generative AI and Predictive AI in the Cloud: Foundational Concepts and Scenarios

Generative AI and Predictive AI in the Cloud: Foundational Concepts and Scenarios Discover this easy-to-understand course for beginners that teaches the fundamentals of generative AI and predictive AI, as well as how they can relate to cloud computing. Provider: LinkedIn Learning Categories: Artificial Intelligence Courses, Machine Learning C.
provider LinkedIn Learning
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California Institute of Technology Coursera

Uso de datos en las organizaciones del S.XXI

Uso de datos en las organizaciones del S.XXI Descripción: Este curso te brinda herramientas prácticas para entender el uso de datos en distintos tipos de organizaciones y así tomar decisiones informadas aplicando prácticas de aseguramiento de calidad, éticas y con una perspectiva inclusiva con la información obtenida. A través.
provider Coursera
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California Institute of Technology Coursera

Enhancing Customer Insights with Generative AI

Enhancing Customer Insights with Generative AI This short course equips marketing professionals, data analysts, and business strategists with practical skills to analyze customer behavior, generate actionable insights, and drive growth using the latest AI tools and real-world case studies. Learn how to seamlessly integrate AI into your business.
provider Coursera
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California Institute of Technology XuetangX

数据与智能技术应用

在数据成为新型生产要素的崭新时代，数据就像新时代的石油一样是重要的、驱动社会的动力和能源。如何让数据真正的为千行万业赋能，这是时代的需求和呼唼。一说到大数据和智能技术，很多非IT类专业出身的学习者往往感到“需要了解，可是太过高深”“零基础的小白，无处下手”。然而，在实际应用中，让专业的人做专业的事是关键。在各行业数智转型的时候，单靠IT出身的专业人士.
provider XuetangX
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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.
provider Udemy
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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.
provider Udemy
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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.
provider Udemy
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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.
provider Udemy

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!