###### tags: `42` `AWS` # 42 SACE WEEK - New Students :::info :bulb: This template is for SACE new students. ::: ## 🎉 Welcome Hi:smile: Welcome to `42 Adelaide` SACE CLOUD Week!! By the time you have finished this week's activities, you will have completed more then 30 hours of AWS Cloud Training! ## :book: AWS Student Information Get to know your AWS Team :small_blue_diamond: **Monica Moorfield**: AWS Skills to Jobs Senior Program Manager [:link:](https://www.linkedin.com/in/monicavanderkley/) :small_blue_diamond: **Arran Peterson**: Solutions Architect [:link:](https://www.linkedin.com/in/arranpeterson/) :small_blue_diamond: **Dylan Thompson**: Solutions Architect / IoT Specialist [:link:](https://www.linkedin.com/in/dylan-thompson-7b6b50123/) :small_blue_diamond: **Justin Brien**: Associate Solutions Architect / IoT Specialist [:link:](https://www.linkedin.com/in/justin-brien/?originalSubdomain=au) :small_blue_diamond: **Brent Sarver**: AWS Skills to Jobs Senior Program Manager [:link:](https://www.linkedin.com/in/brentsarver/) ### AWS Week ### | Day | Time | Topic | |---------|-----------------|-----------------------| | Monday 3 July | 9:30am - 1:15pm | AWS Masterclass| | Tuesday 4 July | 9:30am - 5:00pm | Internet of Things (IoT) | | Wednesday 5 July | 9:30am - 5:00pm | Working with Data Pt1 | | Thursday 6 July | 9:30am - 5:00pm | Working with Data Pt2 | | Friday 7 July | 9:30am - 5:00pm | Project | 8hr | ## :white_check_mark: Checklist ### :small_orange_diamond: Day1 We kick off the week with an AWS Masterclass whereby local AWS Solution Architects will take you through an overview of AWS as a company, and AWS Cloud concepts such as compute, analytics and security. More broadly, students will learn more about career pathways in technology and hear from a range of Amazonians. This is a half day session, so you can spend the afternoon working on your assignments. The day will be delivered as follows: | Workshop | Start Time | Topic | Duration | |---------|-------------------|--------------------|--------| | One | 9:30am | Intro to the week & the team | 45m | | Two | 9:45am| Kahoot! Quiz | 45m | | Three | 10:00am | AWS Cloud 101 | 1.5 hrs | - | **11:30am** | **Break** | **15m** | | Four | 11:45am | Cloud roles quiz | 15m | Five | 12:00pm | Cloud Careers Panel | 1 hr | | - | **1:00pm** | **Day Ends** | - | ### :small_orange_diamond: Day2 Get your hands dirty! The Sustainability IoT Hackathon is a fun way for students to learn about technology. During this all day event, students will learn how to use technology for good and how to program Internet of Things (IoT) devices with a visual programming interface. This will give the students practical experience interacting with IoT devices, such as sensors, buttons and water pumps. The students will also learn how this technology can be used for sustainable agriculture. What will the learners do? * Learn about the [United Nations Sustainability Development Goals](https://sdgs.un.org/goals) and how technology can be used to achieve them * Use collaborative programming methods to learn both hard and soft skills * Program IoT devices with a visual programming language built on Python to allow beginners and experts to work together * Gain confidence that they will be able to succeed in a technology role Workshop: https://catalog.workshops.aws/build-a-builder/en-US The day will be delivered as follows: | Workshop | Start Time | Topic | Duration | |---------|------------------|----------------------|--------| | One | 9:30am | Intro to IoT | 1hr | | - | **10:30am** | **Break** - (Divide into groups) | **15m** | | Two | 10:45am | Set up the Device and Let’s get familiar | 2hr | | - | **12:45pm** | **Break** | **30m** | | Three | 1:15pm | Get Moving - Motion Detector | 30m | | Four | 1:45pm | Feel the temperature of the room | 30m | | - | **2:15pm** | **Break** | **15m** | | Five | 2:30pm | Are you thirsty? Measure the soil moisture of each of our plants| 30m | | Six | 3:00pm | Pump it - Control a pump to supply plants with water | 1hr | | Seven | 4:00pm | Challenge Lab: Put it all together. Automatically water your plant, visualize the state of you plant and turn the lights off when nobody is home| 30m | | Eight | 4:30pm | Open House. Stay to ask questions, finish exploring your project| 30m | | - | **5:00pm** | **Day Ends** | - | All the sections in `Self-watering Plant` **Part 1** and **Part 2** can be done with the equipment available. ![image](https://hackmd.io/_uploads/rkqmWTHYA.png) ### :small_orange_diamond: Day3 Work with data! [AWS Glue DataBrew](https://aws.amazon.com/glue/features/databrew/) is a new visual data preparation tool that makes it easy for data analysts and data scientists to clean and normalise data to prepare it for analytics and machine learning. You can choose from over 250 pre-built transformations to automate data preparation tasks, all without the need to write any code. You can automate filtering anomalies, converting data to standard formats, and correcting invalid values, and other tasks. After your data is ready, you can immediately use it for analytics and machine learning projects. #### Workshop Company ABC is an online pet product retailer. They have recently launched a new product line for pets. They were expecting it to be a great success but sales from some regions were below their expectation. Marketing research suggests that limited awareness about the product in those regions is the main reason for inadequate sales. To address this problem, they want to start a targeted mail campaign in those regions to increase awareness and product sales. The team needs a fast turnaround and they don’t have much time to write code and manage infrastructure. **Actions**: The team needs to analyse and transform customer, product, and sales data to compare and contrast sales of two product lines and identify postcodes where specific product types need to be marketed. The students will perform these tasks and complete the following labs. **Labs** * Profiling and Data Quality * Transforming Data https://catalog.us-east-1.prod.workshops.aws/workshops/6532bf37-3ad2-4844-bd26-d775a31ce1fa/en-US/30-howtostart/workshopstudio The day will be delivered as follows: | Workshop | Start Time | Topic | Duration | |---------|----------|------------------------|----------| | One | 9:30am | Intro to Glue Databrew | 30m | | Two | 10:00am | Profiling and Data Quality | 1hr | | - | **11:00am** | **Break** | **15m** | | Three | 11:15am | Standard Transform | 45m | | - | **12:00pm** | **Break** | **1hr** | | Four | 1:00pm | Advanced Transform | 1hr | | - | **2:00pm** | **Break** | **15m** | | Five | 2:15pm | Project Work or Feature Engineering| 3hr | | - | **5:00pm** | **Day Ends** | - | #### How do I find data for my project? **AWS Data Exchange** Easily find, subscribe to, and use third-party data in the cloud https://aws.amazon.com/data-exchange/ ### :small_orange_diamond: Day4 Amazon SageMaker Canvas expands access to machine learning (ML) by providing students with a visual interface that allows them to generate accurate ML predictions on their own—without requiring any ML experience or having to write a single line of code. With [Amazon SageMaker Canvas](https://aws.amazon.com/sagemaker/canvas/), you can import data from disparate sources, select values you want to predict, automatically prepare and explore data, and quickly and more easily build ML models. You can then analyse models and generate accurate predictions with a few clicks. #### Workshop Self-paced lab that allows students to enable themselves or others into using no-code Machine Learning and Amazon SageMaker Canvas to solve real-world challenges based on publicly available datasets. While it is expected for anyone to be able to use SageMaker Canvas in complete autonomy. **Use Case Labs** * **Prediction Machine Failure Types (Manufacturing)** * **Supply chain delivery on-time (Transport & Logistics)** * Customer Churn (Marketing) * Housing Pricing (Real Estate) * Demand Forecasting (Retail) * Loan Default Prediction (Financial Services) * Diabetic Patient Readmission Prediction (Healthcare) **Technology Labs** * **No-Code Computer Vision** * **No-Code Natural Language Processing (Text Analysis)** * Customer Churn (Marketing) https://catalog.workshops.aws/canvas-immersion-day The day will be delivered as follows: | Workshop | Start Time | Topic | Duration | |---------|-----------------------|------------------------|--------| | One | 9:30am | Intro to Amazon SageMaker Canvas | 30m | | Two | 10:00am | Set the scene for Lab3 | 15m | | Three | 10:15am | Predicting Machine Failure Types (Manufacturing) | 90m | | - | **11:45am** | **Break** | **1hr** | | Four | 12:45pm | Supply chain delivery on-time (Transportation and Logistic) | 90m | | - | **2:15pm** | **Break** | **15m** | | Five | 2:30pm | Technology Labs (*Optional*) or Project| 2hr | | - | **4:30pm** | **Day Ends** | - | ### :small_orange_diamond: Day5 How would you solve one of the [17 UN goals](https://sdgs.un.org/goals) using data to draw your insights? **Outcome**: Present your findings back to the group. ## Assessment You'll be assessed based on the successful completion of your project. --- ## Additional Reading ## * [IT skills training, certifications benefit both organizations and employees](https://aws.amazon.com/blogs/training-and-certification/skillsoft-it-skills-and-salary-report-2022/) * [When cloud curiosity leads to a career transformation](https://aws.amazon.com/blogs/training-and-certification/when-cloud-curiosity-leads-to-a-career-transformation/) * [What's The Difference Between A Data Warehouse, Data Lake, And Data Mart?](https://aws.amazon.com/compare/the-difference-between-a-data-warehouse-data-lake-and-data-mart/) * [Learn About Data analytics](https://aws.amazon.com/training/learn-about/data-analytics/) ## Reference Material ## #### Data Engineering AWS Glue DataBrew Blog Articles * https://aws.amazon.com/blogs/machine-learning/category/analytics/aws-glue-databrew/ #### Machine Learning Amazon SageMaker Canvas Blog Articles * https://aws.amazon.com/blogs/machine-learning/tag/amazon-sagemaker-canvas/ SageMaker Canvas Advanced Metrics deep dive * https://aws.amazon.com/blogs/machine-learning/is-your-model-good-a-deep-dive-into-amazon-sagemaker-canvas-advanced-metrics SageMaker Built-in Algorithms used in Canvas * https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html Building Custom Models in Canvas * https://docs.aws.amazon.com/sagemaker/latest/dg/canvas-custom-models.html ## External Sources ## These resources have been collated from student experience and aren't affiliated with AWS. TBA # FAQ # ### Online Learning ### **What is [AWS Educate](https://www.awseducate.com/)?** * Cloud computing can open the door to exciting opportunities in technology or business. AWS Educate provides simple, barrier-free access to secure, authentic, self-graded labs in the AWS Console with just an email address. Learn, practice, and evaluate cloud skills in real time without creating an Amazon or AWS account. AWS Educate offers hundreds of hours of free, self-paced online resources designed specifically to help pre-professional learners develop in-demand cloud skills. You’re in control of your learning journey: follow personalized content recommendations to earn badges that demonstrate your skill mastery and search the job board to find employers looking to hire for in-demand roles. **What is [AWS Skill Builder](https://explore.skillbuilder.aws/)?** * AWS Skill Builder is a repository of over 700 training lessons to help you learn AWS and refine your knowledge of AWS services and improve your skills so you can put them into practice or apply the knowledge during the many AWS certifications.