Big Data Courses

133 Courses

NEW AWS Certified Data Analytics Specialty DAS C01 Course

Title: NEW AWS Certified Data Analytics Specialty DAS C01 Course Description: Aspiring to ace the NEW AWS Certified Data Analytics Specialty DAS C01 exam with a focus on Machine Learning and AI? Enroll in our comprehensive course on Udowe now! Provider: Udemy Categories: Machine Learning Courses, Big Data Courses, Data Science Courses, Data Visuali.
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provider Udemy
pricing Paid Course
duration 9 hours
sessions On-Demand

The IT Ops Sessions: The Role of AIOps in Building a Digital Immune System

Title: The IT Ops Sessions: The Role of AIOps in Building a Digital Immune System Description: Join us for an enlightenining IT Ops session on "The Role of AIOps in Building a Digital Immurse System," where you'll delve into the transformative impact of artificial intelligence in IT operations. Discover how AIOps employs AI to automate and enhance.
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provider Pluralsight
pricing Free Trial Available
duration 30 minutes
sessions On-Demand

Data Engineering

Organizations today are flooded with data, and the pressing need to transform vast amounts of information into actionable insights has escalated the demand for skilled Data Engineers. Data Engineers are crucial in building and optimizing systems to collect, store, and analyze data, enabling businesses to make strategic decisions based on substantia.
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provider edX  Professional Certificate
pricing $1,196.00
duration 57 weeks, 3-4 hours a week

Learning Power Pivot and SharePoint 2013

Join expert Neicole Crepeau in our upcoming course, "Learning Power Pivot and SharePoint 2013", available exclusively through LinkedIn Learning. This dynamic educational experience promises to deepen your understanding of Excel's Power Pivot and Power View tools, marrying these with the capabilities of SharePoint 2013. Participants will learn how t.
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provider LinkedIn Learning
pricing Free Trial Available
sessions On-Demand

Big Data Analysis Deep Dive

Big Data Analysis Deep Dive As the demand for skilled architects, engineers, and analytics professionals with Big Data expertise grows, our in-depth course offered through Coursera provides you with all the essential skills needed to succeed in this evolving field. Learn data processing using Python. Gain proficiency in writing and reading SQL q.
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provider Coursera
pricing Free Online Course (Audit)
duration 14 hours
sessions On-Demand

Introduction to Data Analytics

Title: Introduction to Data Analytics Description: Are you considering a career in Data Analysis but unsure where to start? Our course offers a comprehensive foundation in Data Analysis, covering the role of a Data Analyst, essential tools, and key responsibilities. Learn from data experts through engaging content filled with insights and practical.
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provider Coursera
pricing Free Online Course (Audit)
duration 10 hours
sessions On-Demand

AWS Analytics - Athena Kinesis Redshift QuickSight Glue

Covering Data Science, Data Lake, Machine learning, Warehouse, Pipeline, Athena, AWS CLI, Big data, EMR and BI, AI tools
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provider Udemy
pricing Free Online Course
duration 2 hours 38 minutes
sessions On-Demand

Data Engineering - ETL, Web Scraping ,Big Data,SQL,Power BI

Data Engineering - ETL, Web Scraping, Big Data, SQL, Power BI | Udemy Course Data Engineering - ETL, Web Scraping, Big Data, SQL, Power BI Unlock the power of data with hands-on interaction techniques in ETL, Web Scraping, Big Data, SQL, and Power BI. This Udemy course offers practical skills to elevate your data engineerin.
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provider Udemy
pricing Paid Course
duration 12 hours 22 minutes
sessions On-Demand

Big Data 101

Big Data 101 Get answers to fundamental questions such as: How do we tackle Big Data? Why are we interested in it? How does Big Data add value to businesses? Offered by Cognitive Class, this course falls under the categories of Big Data Courses, Data Science Courses, and Hadoop Courses. Enroll in Big Data 101 today to start your journey in mas.
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provider Cognitive Class
pricing Free Online Course
duration 3 hours
sessions On-Demand

Módulo Data Analytics, Business Intelligence y Visualización

aprende a realizar un proyecto de datos desde la captura hasta la extracción de conocimiento y visualización en cloud
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provider Udemy
pricing Free Online Course
duration 2 hours 2 minutes
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!