The course will provide a non-technical overview of the artificial intelligence field. Initially, a discussion on the birth of AI is provided, remarking the seminal ideas and preliminary goals. Furthermore, the crucial weaknesses are presented and how these weaknesses have been circumvented. Then, the current state of AI is presented, in terms of goals, importance at national level, and strategies. Moreover, the taxonomy of the AI topics is presented.

In this 1-hour long project-based course, you will learn how to identify the concept of business digital transformation, as well as the different types of business digitization, how to determine the role of customer support in your company and identify the customer support processes, how define Customer Relationship Management (CRM) and interpret the importance of using it in your business context and how to customize your own CRM using the HubSpot CRM tool. It will also give you the know-how of evaluating the alignment between your customer support digital transformation and your existing business strategy. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

In this course, you will be introduced to foundational programming skills with basic Python Syntax. You’ll learn how to use code to solve problems. You’ll dive deep into the Python ecosystem and learn popular modules, libraries and tools for Python. You’ll also get hands-on with objects, classes and methods in Python, and utilize variables, data types, control flow and loops, functions and data structures. You’ll learn how to recognize and handle errors and you’ll write unit tests for your Python code and practice test-driven development. By the end of this course, you will be able to: • Prepare your computer system for Python programming • Show understanding of Python syntax and how to control the flow of code • Demonstrate knowledge of how to handle errors and exceptions • Explain object-oriented programming and the major concepts associated with it • Explain the importance of testing in Python, and when to apply particular methods This is a beginner course for learners who would like to prepare themselves for a career in back-end development or database engineering. To succeed in this course, you do not need prior web development experience, only basic internet navigation skills and an eagerness to get started with coding.

In this one hour long project, you will learn everything you need to know to start working with Azure backup. We will begin by setting up a Recovery Services Vault where Azure stores all the backup data and then we will create backup policies. In the latter part of the course, we will create a Free tier virtual machine and we will implement an entire virtual machine backup. By the end of this course, you will gain the ability to utilize the Azure cloud for all of your backup needs.

This is a self-paced lab that takes place in the Google Cloud console. Cloud Dataprep by Trifacta is an intelligent data service for visually exploring, cleaning, and preparing structured and unstructured data for analysis. In this lab you will explore the Cloud Dataprep UI to build a data transformation pipeline.

This course will teach you how to perform data analysis using MongoDB's powerful Aggregation Framework. You'll begin this course by building a foundation of essential aggregation knowledge. By understanding these features of the Aggregation Framework you will learn how to ask complex questions of your data. This will lay the groundwork for the remainder of the course where you'll dive deep and learn about schema design, relational data migrations, and machine learning with MongoDB. By the end of this course you'll understand how to best use MongoDB and its Aggregation Framework in your own data science workflow.

During this learning journey, you will be learning how to apply modernization in your Hybrid Cloud environment including IBM Z. We will look at lifecycle enablement by using DevOps, how to create an application centric environment, Establishing Data Centric Integration and utilize events to drive responses. By using digital content, use cases and hands-on exercises we provide theability to look and learn what it takes to achieve and implement modernization in the best way possible.

In this project you will use the Modeling and Design Tool in MySQL Workbench to design and create a multiple-table relational database. As a DBMS (database management system), MySQL is used by many organizations for managing a variety of types and sizes of databases. MySQL Workbench acts as an integrated development environment allowing users to work with relational databases using a visual user interface rather than the command line. Hands-on activities include using the Modeling and Design Tool to draw a database design diagram, generating the database from that diagram, and then using MySQL Workbench features to load data into the database tables. You will also find an optional Challenge Task and an optional Capstone task for extra practice. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Welcome to the SAS Programming for Distributed Computing in SAS Viya course. SAS Viya is an AI, analytic and data management platform running on a scalable, distributed, cloud-native architecture. In this course you will learn how to modify existing Base SAS programs to execute in SAS Viya. The programs you create will leverage the power of SAS Cloud Analytic Services (CAS) to access, manage, and analyze in-memory tables. This is an advanced course, intended for learners with SAS programming experience. To be successful, you should be able to access data via SAS libraries, read and prepare data with the DATA step, query data using PROC SQL, and summarize data with the MEANS and FREQ procedures. This foundational knowledge can be acquired in the Coursera SAS Programmer specialization. By the end of the course, you will be able to: - Load data into SAS Cloud Analytic Services - Modify DATA step and SQL procedure code to execute in CAS - Use CAS-enabled procedures - Write CASL code to execute CAS actions

This is a self-paced lab that takes place in the Google Cloud console. In this lab you will use Liquid parameters and templated filters to enhance interactivity by users in Looker.