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Big Data Courses

170 Courses

California Institute of Technology Udemy

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

Data Engineering - ETL, Web Scraping, Big Data, SQL, Power BI | Udemy Join our expert-led course on Udemy to gain practical experience in data interaction using key tools and technologies like ETL, web scraping, big data, SQL, and Power BI. Designed for those looking to enhance their data engineering skills, this course provides immersi.
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California Institute of Technology Udemy

Big Data: Hadoop| MapReduce| Hive| Pig| NoSQL| Mahout| Oozie

Unlock the potential of Big Data with this expert-led course on Udemy. Dive into the world of Hadoop and its ecosystem, including HDFS, MapReduce, Hive, Pig, and NoSQL databases. Extend your skills further with Mahout for machine learning, Oozie for workflow scheduling, and Flume for data ingestion. Enhance your capabilities with practical ex.
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California Institute of Technology Udemy

Master Course in Data Visualization & Data Warehousing (101)

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California Institute of Technology Udemy

Modeling Data Warehouse with Data Vault 2.0

Immerse yourself in the foundational aspects of Data Vault 2.0, as this course takes you through the core principles of agile methodologies and big data management. Tailored for those with a keen interest in big data, project management, and data warehousing, this course offers an insightful journey into data modeling intricacies. Hosted on.
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California Institute of Technology XuetangX

人工智能教育应用

人工智能被视为继蒸汽机、电力、互联网之后最有可能带来新的产业革命浪潮的技术，而教育领域则是人工智能技术影响最为深刻的领域之一。无论你是在校学生还是一线教师，只要对人工智能和教育感兴趣，都可以来学习这门课程。这门课程将介绍人工智能的核心技术与教育创新应用场景，帮助你深刻认识人工智能对教育体系的变革与推动作用，以及未来人工智能在教育领域的发展趋势.
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California Institute of Technology Northeastern University

Database to AI: Practical Data Analytics Integration

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California Institute of Technology Udemy

AWS Analytics - Athena Kinesis Redshift QuickSight Glue

Unlock the potential of AWS Analytics with our comprehensive course covering key topics such as Athena, Kinesis, Redshift, QuickSight, and Glue. Gain insights into the latest trends in Data Science, develop robust Data Lakes, and master Machine Learning techniques. Our course is designed for professionals looking to enhance their knowledge in.
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California Institute of Technology Pluralsight

NoSQL: The Big Picture

Join us for an in-depth exploration of NoSQL: The Big Picture. This comprehensive presentation offers a thorough understanding of NoSQL technology, its impact on businesses, and provides guidelines for successful adoption. This executive briefing delves into the popularity of NoSQL databases, highlighting their advantages and areas where they.
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California Institute of Technology XuetangX

数据科学导论

新技术如云计算、大数据、物联网和人工智能彻底改变了我们对数据的理解，带来了许多新问题，而这些问题在传统理论中尚无解决方案。每个领域现在已发展出许多新的学科如农业大数据、工业大数据等，从学科角度探讨大数据的挑战和解决方案。因此，我们亟需更新我们的知识结构。 课程介绍数据科学的基本概念、理论，并展示其应用和发展前景。学生将掌握获取、处理、管理、分析和.
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California Institute of Technology XuetangX

工业互联网

1. 课程所属学科专业 《工业互联网》属于交叉学科课程，涵盖多个专业领域：0802 机械工程, 0804 仪器科学与技术, 0808 电气工程, 0809 电子科学与技术, 0810 信息与通信工程, 0811 控制科学与工程, 0812 计算机科学与技术, 0822 轻工技术与工程, 0835 软件工程, 0837 安全科学与工程, 0839 网络空间安全, 0854 电子信息, 0855 机械, 1201管理科学与工程, 1205 信息资源.
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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!