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Big Data Courses

207 Courses

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California Institute of Technology Stanford University

Introduction to Computers - Stanford University

Embark on a comprehensive journey into the world of computers with "Introduction to Computers" offered by Stanford University, now available on YouTube. This meticulously designed course provides a foundation in the essentials of computer science and technology, catering specifically to beginners. Dive into a broad array of topics, including the bi.
provider YouTube
sessions On-Demand
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California Institute of Technology KTH Royal Institute of Technology

Big Data

Delve into the world of Big Data, a field flourishing with zettabytes of data collected yearly. In an age where information is abundant, the challenge lies not just in accessing data but in sifting through it to uncover meaningful insights and trends critical for making informed business decisions. Discover the power of big data analytics and data.
provider Coursera  MasterTrack
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California Institute of Technology Tel Aviv University

Digital Governance

Explore the realm of Digital Governance with this comprehensive MOOC provided by Coursera and designed by Tel Aviv University. Delve into the world where big data, artificial intelligence (AI), machine learning, autonomous vehicles, and chatbots have become integral to our professional, legal, and political lexicon. As technology seamlessly integra.
provider Coursera
sessions On-Demand
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California Institute of Technology National Chiao Tung University

Introduction to Digital health

Embark on a comprehensive journey through the realm of digital health with our introductory course offered by National Chiao Tung University, now available on Coursera. Dive deep into the core concepts and definitions that shape the rapidly evolving digital health landscape. Explore a wide array of topics from Learning Health Systems and Electronic.
provider Coursera
sessions On-Demand
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California Institute of Technology University of Florida

Big Data for Agri-Food: Principles and Tools

Unlock the power of big data in the agri-food sector with our comprehensive course, Big Data for Agri-Food: Principles and Tools. Delve into the complexities of modern big data technologies and lay the groundwork for understanding how principles like immutability and pure functions facilitate parallel data processing. This essential knowledge is cr.
provider edX
sessions On-Demand
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California Institute of Technology Independent

Fundamentals of Deep Learning for Computer Vision

Embark on a journey into the world of AI with our hands-on course, "Fundamentals of Deep Learning for Computer Vision." This comprehensive course is designed for those eager to grasp the essentials of deep learning, focusing on training and deploying neural networks to solve real-world challenges. Throughout the course, participants will: Learn to.
provider Independent
sessions On-Demand
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California Institute of Technology LinkedIn Learning

Big Data in the Age of AI

Delve into the expansive realm of Big Data and its pivotal role in the current era dominated by Artificial Intelligence (AI). This comprehensive course, offered by LinkedIn Learning and tailored for enthusiasts from various backgrounds, sheds light on the intricate mechanisms of big data. Participants will uncover the synergistic relationship betwe.
provider LinkedIn Learning
sessions On-Demand
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California Institute of Technology Indiana University

Business Excellence in a knowledge-driven Industry 4.0 world

Discover how to navigate the complexities of business excellence in the dynamically digital landscape of Industry 4.0 with our comprehensive program. As we step into an era where societies are interlinked through digitalization, it's predicted that by 2025, the web will host a staggering 175 zetabytes of digital assets. These assets range from data.
provider edX  Professional Certificate
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California Institute of Technology Universitat Oberta de Catalunya

Data Analysis for Decision-Making

Demand for data analysis skills in the U.S. is forecasted to surge by 21% over the coming decade, quadrupling the growth rate of the overall job market. With fields such as Data Science, Data Analytics, and Statistics poised for up to 34% growth, the global competition for talent in these areas is intensifying, fueled by an expanding demand across.
provider edX  Professional Certificate
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California Institute of Technology University of Michigan

Data Science Ethics

Delve into the complexities of Data Science Ethics with the University of Michigan's cutting-edge course, available on Coursera. This educational journey sheds light on the critical ethical considerations surrounding the privacy and control of consumer information and big data. The course emerges as particularly relevant in the wake of recent large.
provider Coursera
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!