Learn Object-oriented Programming in Python-beginner-level! (Exercises + cheat sheets + better Coding)!
Duration 5 Days 30 CPD hours This course is intended for This hands-on course is geared for experienced DBAs with basic Oracle 19c skills. Overview This course combines expert lecture, real-world demonstrations and group discussions with machine-based practical labs andexercises. Working in a hands-on learning environment led by our expert facilitator, students will explore: Creating CDBs and Regular PDBs Managing CDBs and PDBs Backup and Duplicate Upgrading and Transporting CDBs and Regular PDBs Backup Strategies and Terminology Restore and Recovery Concepts Using Flashback Technologies Duplicating a Database Installing Grid Infrastructure and Oracle Database Patching Grid Infrastructure and Oracle Database Upgrading to Oracle Grid Infrastructure Using General Overall Database Enhancements Monitoring and Tuning Database Performance Managing Application PDBs Managing Security in Multitenant databases Recovery and Flashback Configuring and Using RMAN Diagnosing Failures Performing Recovery Transporting Data RMAN Troubleshooting and Tuning Creating an Oracle Database by using DBCA Oracle Restart Upgrading the Oracle Database Installing Grid Infrastructure for a Standalone server Using Availability Enhancements Tuning SQL Statements Geared for participants experienced with Oracle 19c DBA essentials Oracle 19c Database Administration II (Oracle DBA II) expands their understanding of Oracle database administration. Throughout the course students will explore coverage of Multitenant (CDB/PDB), database tuning, SQL tuning, and backup and recovery: the skills needed to keep a database running reliably and efficiently. The current release of the database is used for exercises and demonstrations, and the content back-ported as necessary for previous releases. Creating CDBs and Regular PDBs Configure and create a CDB Create a new PDB from the CDB seed Explore the structure of PDBs Manage CDBs and PDBs Manage PDB service names and connections Manage startup, shutdown and availability of CDBs and PDBs Change the different modes and settings of PDBs Evaluate the impact of parameter value changes Performance management in CDBs and PDBs Control CDB and PDB resource usage with the Oracle Resource Manager Backup and Duplicate Perform Backup and Recover CDBs and PDBs Duplicate an active PDB Duplicate a Database Upgrading and Transporting CDBs and Regular PDBs Upgrade an Oracle Database Transport Data Backup Strategies and Terminology Perform Full and Incremental Backups and Recoveries Compress and Encrypt RMAN Backups Use a media manager Create multi-section backups of exceptionally large files Create duplexed backup sets Create archival backups Backup of recovery files Backup non database files Back up ASM meta data Restore and Recovery Concepts Employ the best Oracle Database recovery technology for your failure situation Describe and use Recovery technology for Crash, Complete, and Point-in-time recovery Using Flashback Technologies Configure your Database to support Flashback Perform flashback operations Duplicating a Database Duplicate Databases Install Grid Infrastructure and Oracle Database Install Grid Infrastructure for a Standalone server Install Oracle Database software Patching Grid Infrastructure and Oracle Database Patch Grid Infrastructure and Oracle Database Upgrading to Oracle Grid Infrastructure Upgrade Oracle Grid Infrastructure Using General Overall Database Enhancements Install Oracle Database software Create, Delete and Configure Databases using DBCA Creating CDBs and Regular PDBs Use Miscellaneous 19c New Features Monitoring and Tuning Database Performance Managing Memory Components Understanding the Automatic Workload Repository (AWR) Understanding the Advisory Framework Monitoring Wait Events, Sessions, and Services Managing Metric Thresholds and Alerts Understanding and Using the Performance Tuning Methodology Performing Performance Planning Understanding the Automatic Database Diagnostic Monitor (ADDM) Manage Application PDBs Explain the purpose of application root and application seed Define and create application PDBs Install, upgrade and Patch applications Create and administer Application PDBS Clone PDBs and Application containers Plug and unplug operations with PDBs and application containers Comparing Local Undo Mode and Shared Undo Mode Manage Security in Multitenant databases Manage Security in Multitenant databases Manage PDB lockdown profiles Audit Users in CDBs and PDBs Manage other types of policies in application containers Recovery and Flashback Restore and Recovering Databases with RMAN Perform CDB and PDB flashback Configuring and Using RMAN Configure RMAN and the Database for Recoverability Configure and Using an RMAN recovery catalog Diagnosing Failures Detect and repair database and database block corruption Diagnosing Database Issues Performing Recovery Restore and Recovering Databases with RMAN Perform Non RMAN database recovery Transporting Data Transport Data RMAN Troubleshooting and Tuning Interpret the RMAN message output Diagnose RMAN performance issues Creating an Oracle Database by using DBCA Create, Delete and Configure Databases using DBCA Oracle Restart Configure and use Oracle Restart to manage components Upgrade the Oracle Database Plan for Upgrading an Oracle Database Upgrade an Oracle Database Perform Post-Upgrade tasks Install Grid Infrastructure for a Standalone server Rapid Home Provisioning Using Availability Enhancements Use an RMAN recovery catalog Use Flashback Database Tuning SQL Statements Understanding the Oracle Optimizer Using the SQL Tuning Advisor Managing Optimizer Statistics Using the SQL Access Advisor Understanding the SQL Tuning Process Additional course details: Nexus Humans Oracle 19c Database Administration II (DBA II) (TTOR20619) 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 Oracle 19c Database Administration II (DBA II) (TTOR20619) 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.
This course is focused on concepts of Python Boto3 Module and Lambda using Python. It covers how to use Boto3 module, concepts of Boto3 (session, resource, client, meta, collections, waiters, and paginators), and AWS Lambda to build real-time tasks with lots of step-by-step examples.
Learn how you can develop and deploy Java, Python, NodeJS Lambda Functions and manage them using Python and Boto3!
Are you looking for a way to boost your productivity and efficiency with Excel? Do you want to learn how to create, analyze and visualize data in powerful and versatile spreadsheets? If so, then our level 2 online Excel course is perfect for you! This course will teach you how to use advanced functions, formulas, charts, tables, pivot tables and macros in Excel. You will learn how to work with large datasets, automate tasks, perform data analysis and create professional reports and dashboards. You will also get tips and tricks to optimize your workflow and save time. The course is suitable for anyone who has some basic knowledge of Excel and wants to take their skills to the next level. You will have access to video lectures, exercises, quizzes and downloadable resources. You will
Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies
Master essential and advanced video editing techniques with our comprehensive Video Editing Tips & Tricks course. Learn to cut, sequence, and polish raw footage, apply creative effects, and enhance your editing skills. Ideal for beginners and experienced editors alike, this course prepares you for diverse career paths in video editing and multimedia production. Enroll today to start creating professional-quality videos!
Be prepared, not paranoid! Course curriculum What are we going to teach you? 1 Instructions for this course Enrollment Process Trouble Shooting 2 Welcome to Safety, Security & Situational Awareness for Women How to use the course player 3 Let's get started! The Why Lesson 1 - Introduction to Safety, Security, Situational Awareness for Women Lesson 2 - Principles of Real-time Behaviour Lesson 3 - How to Recognise Threats through Behaviour Observation Test Lesson 4 - The Predator Mindset Lesson 5- The Dynamics of the Brain Lesson 6 - Indicators of Spiking, Common Date Rape Narcotics and their Effects. Lesson 7 - Colour Coded Risk Evaluation Final Assessment Training and Evaluation Feedback Form 4 Next Steps... Before you go... Recommended Reading List
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