1318 Scientist courses

Thinking about learning Ethics in IT? The BCS Foundation Award in Understanding Ethical Principles in the IT Profession explore ethics in relation to your own role and the ethical principles upheld within the IT profession. It identifies common threats to ethical behaviour in IT and the safeguards that can help to minimise these threats. It also explores the role of legislation and corporate governance in ensuring ethical standards are promoted and maintained You will learn an understanding of The Importance of Ethics to Society, Business and IT Professionals, knowledge of The Ethical Behaviour Required by IT Professional, understanding The Role of Corporate Governance, understand Relevant Legislation and understand Ethical Dilemmas And Safeguards.

Thinking about learning about Knowledge-Based Systems? The BCS Foundation Certificate in Artificial Intelligence teaches learners to recognise Knowledge-Based Systems (such as chat bots), gain an understanding of how they work, and consider how they can add value to an organisation. This award will also enable candidates to understand the concept of Uncertainty and Fuzzy Logic, and how Knowledge-Based Systems can be used to help organisations to make decisions and act where there is higher level of uncertainty. You will learn an understanding of Knowledge-Based Systems and their role within AI, the use of rules within a Knowledge-Based System, an understanding of the principles of case-based reasoning, an understanding of uncertainty and the use of fuzzy logic and an understanding of the role of the inference engine.

Thinking about learning more about the ethical use of AI? The BCS Foundation Award; Understanding the Role of Ethics in the Responsible Use of AI, explores the responsibility of organisations and society towards ensuring AI is implemented for the good of others. It considers the potential harm AI may pose, and the safeguards that can be implemented to ensure it is used safely, ethically and for the good of society. You will be encouraged to explore the benefits associated with AI and the potential value it can add towards the continued evolution of humankind if managed well You will learn learn about the impact and level of responsibility of AI in business, an understanding of the need to scale up the impact and responsibility of AI to society, understand the potential harm and safeguards and understand the role of humans in an AI world.

Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure. In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage. Prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Introduction to data engineering on Azure What is data engineering Important data engineering concepts Data engineering in Microsoft Azure 2 - Introduction to Azure Data Lake Storage Gen2 Understand Azure Data Lake Storage Gen2 Enable Azure Data Lake Storage Gen2 in Azure Storage Compare Azure Data Lake Store to Azure Blob storage Understand the stages for processing big data Use Azure Data Lake Storage Gen2 in data analytics workloads 3 - Introduction to Azure Synapse Analytics What is Azure Synapse Analytics How Azure Synapse Analytics works When to use Azure Synapse Analytics 4 - Use Azure Synapse serverless SQL pool to query files in a data lake Understand Azure Synapse serverless SQL pool capabilities and use cases Query files using a serverless SQL pool Create external database objects 5 - Use Azure Synapse serverless SQL pools to transform data in a data lake Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement Encapsulate data transformations in a stored procedure Include a data transformation stored procedure in a pipeline 6 - Create a lake database in Azure Synapse Analytics Understand lake database concepts Explore database templates Create a lake database Use a lake database 7 - Analyze data with Apache Spark in Azure Synapse Analytics Get to know Apache Spark Use Spark in Azure Synapse Analytics Analyze data with Spark Visualize data with Spark 8 - Transform data with Spark in Azure Synapse Analytics Modify and save dataframes Partition data files Transform data with SQL 9 - Use Delta Lake in Azure Synapse Analytics Understand Delta Lake Create Delta Lake tables Create catalog tables Use Delta Lake with streaming data Use Delta Lake in a SQL pool 10 - Analyze data in a relational data warehouse Design a data warehouse schema Create data warehouse tables Load data warehouse tables Query a data warehouse 11 - Load data into a relational data warehouse Load staging tables Load dimension tables Load time dimension tables Load slowly changing dimensions Load fact tables Perform post load optimization 12 - Build a data pipeline in Azure Synapse Analytics Understand pipelines in Azure Synapse Analytics Create a pipeline in Azure Synapse Studio Define data flows Run a pipeline 13 - Use Spark Notebooks in an Azure Synapse Pipeline Understand Synapse Notebooks and Pipelines Use a Synapse notebook activity in a pipeline Use parameters in a notebook 14 - Plan hybrid transactional and analytical processing using Azure Synapse Analytics Understand hybrid transactional and analytical processing patterns Describe Azure Synapse Link 15 - Implement Azure Synapse Link with Azure Cosmos DB Enable Cosmos DB account to use Azure Synapse Link Create an analytical store enabled container Create a linked service for Cosmos DB Query Cosmos DB data with Spark Query Cosmos DB with Synapse SQL 16 - Implement Azure Synapse Link for SQL What is Azure Synapse Link for SQL? Configure Azure Synapse Link for Azure SQL Database Configure Azure Synapse Link for SQL Server 2022 17 - Get started with Azure Stream Analytics Understand data streams Understand event processing Understand window functions 18 - Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics Stream ingestion scenarios Configure inputs and outputs Define a query to select, filter, and aggregate data Run a job to ingest data 19 - Visualize real-time data with Azure Stream Analytics and Power BI Use a Power BI output in Azure Stream Analytics Create a query for real-time visualization Create real-time data visualizations in Power BI 20 - Introduction to Microsoft Purview What is Microsoft Purview? How Microsoft Purview works When to use Microsoft Purview 21 - Integrate Microsoft Purview and Azure Synapse Analytics Catalog Azure Synapse Analytics data assets in Microsoft Purview Connect Microsoft Purview to an Azure Synapse Analytics workspace Search a Purview catalog in Synapse Studio Track data lineage in pipelines 22 - Explore Azure Databricks Get started with Azure Databricks Identify Azure Databricks workloads Understand key concepts 23 - Use Apache Spark in Azure Databricks Get to know Spark Create a Spark cluster Use Spark in notebooks Use Spark to work with data files Visualize data 24 - Run Azure Databricks Notebooks with Azure Data Factory Understand Azure Databricks notebooks and pipelines Create a linked service for Azure Databricks Use a Notebook activity in a pipeline Use parameters in a notebook Additional course details: Nexus Humans DP-203T00 Data Engineering on Microsoft Azure training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the DP-203T00 Data Engineering on Microsoft Azure course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

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Course Overview This comprehensive Data Analytics course provides an in-depth exploration of data analysis, covering the essential principles and techniques used to extract valuable insights from data. Learners will engage with core concepts, such as data mining, statistical analysis, and visualisation, enabling them to make informed decisions and drive business outcomes. By the end of the course, participants will have the skills to analyse and interpret data, apply analytical tools effectively, and present their findings clearly. This course equips learners with the necessary tools to understand and leverage data in various professional settings, adding significant value to their career prospects. Course Description The Data Analytics course covers a wide range of topics, including the fundamentals of data analysis, statistical methods, and various data visualisation techniques. Learners will explore essential tools such as Excel and specialised software, while gaining a deep understanding of how to collect, store, and process data effectively. Emphasis is placed on developing the analytical mindset required to interpret data accurately and draw actionable insights. This course is designed to ensure learners can confidently navigate the world of data analytics and apply their knowledge in diverse industries, enhancing their problem-solving and decision-making abilities. Course Modules Module 01: Introduction to the World of Data Module 02: Basics of Data Analytics Module 03: Statistics for Data Analytics Module 04: Actions Taken in the Data Analysis Process Module 05: Gathering the Right Information Module 06: Storing Data Module 07: Data Mining Module 08: Excel for Data Analytics Module 09: Tools for Data Analytics Module 10: Data-Analytic Thinking Module 11: Data Visualisation That Clearly Describes Insights Module 12: Data Visualisation Tools (See full curriculum) Who is this course for? Individuals seeking to enhance their analytical skills for data-driven decision-making. Professionals aiming to transition into data analytics or enhance their data-related roles. Beginners with an interest in understanding data and its applications across industries. Business professionals seeking to leverage data for strategic growth. Career Path Data Analyst Business Intelligence Analyst Data Scientist Market Research Analyst Operations Analyst Financial Analyst Business Analyst Data Visualisation Specialist

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