Bases de Dados Relacionais, Análise e Linguagem SQL
- Introdução a Bases de Dados
- Ambientes de Bases de Dados
- Terminologia de Bases de Dados Relacionais
- Planeamento e Desenho de Bases de Dados
- Introdução ao SQL Server
- Criação de Bases de Dados
- Tabelas e Integridade de Dados
- Fundamentos de Transact SQL
- Filtrar e Ordenar Dados
Projeto I (início): Primeira parte de projeto prático
Auto-estudo dedicado a Fundamentos de Querying com Transact-SQL
Neste momento de auto-estudo ser-te-ão facultados guiões, ou materiais, que servirão como um roteiro valioso durante a tua jornada individual de aprendizagem e que serão focados nestes tópicos:
- Introduction to Transact-SQL
- Sort and filter results in T-SQL
- Combine multiple tables with JOINs in T-SQL
- Write Subqueries in T-SQL
- Use built-in functions and GROUP BY in Transact-SQL
- Modify data with T-SQL
Querying Data with Transact-SQL
- Using Set Operators
- Using Table Expressions
- Using Window Ranking, Offset, and Aggregate Functions
- Pivoting and Grouping Sets
- Error Handling
- Transactions
Projeto II (continuação): Continuação do projeto prático iniciado
SQL Database: Development
- Introduction to Database Development
- Designing and Implementing Tables
- Advanced Table Designs
- Ensuring Data Integrity through Constraints
- Introduction to Indexes
- Designing Optimized Index Strategies
- Columnstore Indexes
- Designing and Implementing Views
- Designing and Implementing Stored Procedures
- Designing and Implementing User-Defined Functions
- Responding to Data Manipulation via Triggers
- Using In-Memory Tables
Projeto III (continuação): Continuação do projeto prático iniciado
SQL Database: Infrastructure Administration
- Pre-Requisites for Installing SQL Server
- Installing SQL Server
- Authenticating and Authorizing Users
- Assigning Server and Database Roles
- Authorizing Users to Access Resources
- SQL Server Recovery Models
- Backup of SQL Server Databases
- Restoring SQL Server Databases
- Automating SQL Server Management
- Configuring Security for SQL Server Agent
- Monitoring and Troubleshooting SQL Server
- Working with Databases
- Managing Index Fragmentation
- Performing Database Maintenance
- High Availability
Projeto IV (Final): Conclusão do projeto prático
Azure Fundamentals (AZ-900) – E-Learning
- Describe core Azure concepts
- Describe core Azure services
- Describe core solutions and management tools on Azure
- Describe general security and network security features
- Describe identity, governance, privacy, and compliance features
- Describe Azure cost management and service level agreements
Microsoft Azure Data Fundamentals (DP-900)
- Explore core data concepts
- Explore relational data in Azure
- Explore non-relational data in Azure
- Explore modern data warehouse analytics in Azure
Administering Relational Databases on Microsoft Azure (DP-300)
- Plan and implement data platform resources
- Implement a secure environment
- Monitor and optimize operational resources
- Optimize query performance
- Perform automation of tasks
- Plan and implement a High Availability and Disaster Recovery (HADR) environment
Ação de preparação para exame DP-300
Implementing a SQL Data Warehouse
- Introduction to Data Warehousing
- Designing and Implementing a Data Warehouse
- Implementing an Azure SQL Data Warehouse
- Creating an ETL Solution
- Implementing Control Flow in an SSIS Package
- Debugging and Troubleshooting SSIS Packages
- Implementing an Incremental ETL Process
- Extending SQL Server Integration Services (SSIS)
- Deploying and Configuring SSIS Packages
Projeto I (2.1 – início): Primeira parte do 2º projeto prático
Auto-estudo dedicado a Python para Data Science
Neste momento de auto-estudo ser-te-ão facultados guiões, ou materiais, que servirão como um roteiro valioso durante a tua jornada individual de aprendizagem e que serão focados nestes tópicos:
- Python Basics
- Python Lists
- Functions and Packages
- Matplotlib
- Control flow and Pandas
Introduction to Big Data Administration
- Introduction to Big Data;
- Hadoop (Data Management);
- Hive, Pig (Data Access);
- Impala (Data Analysis);
- Flume, Sqoop (Data Integration)
Projeto II (2.2 continuação): Continuação do projeto prático iniciado
Data Engineering on Microsoft Azure (DP-203)
- Explore compute and storage options for data engineering workloads
- Run interactive queries using Azure Synapse Analytics serverless SQL pool
- Data exploration and transformation in Azure Databricks
- Explore, transform, and load data into the data warehouse using Azure Synapse Analytics Apache Spark
- Ingest and load data into the data warehouse
- Transform data with Azure Data Factory or Azure Synapse Pipelines
- Orchestrate data movement and transformation in Azure Data Factory or Azure Synapse Pipelines
- End-to-end security with Azure Synapse Analytics
- Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
- Real-time stream processing with Azure Stream Analytics
- Create a stream processing solution with Event Hubs and Azure Databricks
Projeto III (2.3 fim): Conclusão do projeto prático
Ação de preparação para exame DP-203
Microsoft Power Platform Fundamentals (e-Learning)
- Introduction to Microsoft Power Platform
- Introduction to Dataverse
- Introduction to Power Apps
- How to build a canvas app
- How to build a model-driven app
- Introduction to Power Apps portals
- Introduction to Power Automate
- How to build an automated solution
- Introduction to Power BI
- How to build a simple dashboard
- Introduction to Power Virtual Agents
- How to build a basic chatbot
Microsoft Power BI Data Analyst (PL-300)
- Get Started with Microsoft Data Analytics
- Prepare Data in Power BI
- Clean, Transform, and Load Data in Power BI
- Design a Data Model in Power BI
- Create Model Calculations using DAX in Power BI
- Optimize Model Performance in Power BI
- Create Reports in Power BI
- Create Dashboards in Power BI
- Enhance reports for usability and storytelling in Power BI
- Perform Advanced Analytics in Power BI
- Manage Datasets in Power BI
- Create and Manage Workspaces in Power BI
Análise Estatística
- Princípios essenciais de estatística
- A estatística ao serviço dos dados e da informação
Designing and Implementing a Data Science Solution on Azure (DP-100)
- Getting Started with Azure Machine Learning
- Visual Tools for Machine Learning
- Running Experiments and Training Models
- Working with Data
- Working with Compute
- Orchestrating Operations with Pipelines
- Deploying and Consuming Models
- Training Optimal Models
- Responsible Machine Learning
- Monitoring Models
Ação de preparação para exame DP-100
Microsoft Azure AI Fundamentals (AI-900) – E-Learning
- Introduction to AI
- Machine Learning
- Computer Vision
- Natural Language Processing
- Conversational AI
Designing and Implementing a Microsoft Azure AI Solution (AI-102)
- Introduction to AI on Azure
- Developing AI Apps with Cognitive Services
- Getting Started with Natural Language Processing
- Building Speech-Enabled Applications
- Creating Language Understanding Solutions
- Building a Q&A Solution
- Conversational AI and the Azure Bot Service
- Getting Started with Computer Vision
- Developing Custom Vision Solutions
- Detecting, Analyzing, and Recognizing Faces
- Reading Text in Images and Documents
- Creating a Knowledge Mining Solution
Certificação Rumos Expert (CRE): Azure Data Scientist
Certificação com base num projeto prático apresentado, onde será necessário utilizar os conceitos apreendidos ao longo de toda a Academia
