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If you are someone wishing to learn to code in Python, then this is just what you need. This course will help you build a solid foundation in coding with Python 3. It includes lots of opportunities for practice that will help put your learnings into action!

Duration 3 Days 18 CPD hours This course is intended for This course is intended for information workers and data science professionals who seek to use database reporting and analysis tools such as Microsoft SQL Server Reporting Services, Excel, Power BI, R, SAS and other business intelligence tools, and wish to use TSQL queries to efficiently retrieve data sets from Microsoft SQL Server relational databases for use with these tools. Overview Identify independent and dependent variables and measurement levels in their own analytical work scenarios. Identify variables of interest in relational database tables. Choose a data aggregation level and data set design appropriate for the intended analysis and tool. Use TSQL SELECT queries to produce ready-to-use data sets for analysis in tools such as PowerBI, SQL Server Reporting Services, Excel, R, SAS, SPSS, and others. Create stored procedures, views, and functions to modularize data retrieval code. This three-day instructor-led course is about writing TSQL queries for the purpose of database reporting, analysis, and business intelligence. Specifically, this course presents TSQL within the context of data analysis in other words, making meaning from the data rather than transaction-oriented data-tier application development. The course starts with a brief discussion of levels of measurement and quantitative research methodogy, and integrates these concepts into each TSQL topic presented. The goal is to provide a consistent, direct, and purposeful learning path from RDBMS data retrieval through analytical tools such as SQL Server Reporting Services, PowerBI, Excel, R, SAS, and SPSS. Module 1: Introduction to TSQL for Business Intelligence Two Approaches to SQL Programming TSQL Data Retrieval in an Analytics / Business Intelligence Environment The Database Engine SQL Server Management Studio and the CarDeal Sample Database Identifying Variables in Tables SQL is a Declarative Language Introduction to the SELECT Query Module 2: Turning Table Columns into Variables for Analysis: SELECT List Expressions, WHERE, and ORDER BY Turning Columns into Variables for Analysis Column Expressions, Data Types, and Built-in Functions Column aliases Data type conversions Built-in Scalar Functions Table Aliases The WHERE clause ORDER BY Module 3: Combining Columns from Multiple Tables into a Single Dataset: The JOIN Operators Primary Keys, Foreign Keys, and Joins Understanding Joins, Part 1: CROSSJOIN and the Full Cartesian Product Understanding Joins, Part 2: The INNERJOIN Understanding Joins, Part 3: The OUTERJOINS Understanding Joins, Part 4: Joining more than two tables Understanding Joins, Part 5: Combining INNER and OUTERJOINs Combining JOIN Operations with WHERE and ORDER BY Module 4: Creating an Appropriate Aggregation Level Using GROUP BY Identifying required aggregation level and granularity Aggregate Functions GROUP BY HAVING Order of operations in SELECT queries Module 5: Subqueries, Derived Tables and Common Table Expressions Non-correlated and correlated subqueries Derived tables Common table expressions Module 6: Encapsulating Data Retrieval Logic Views Table-valued functions Stored procedures Creating objects for read-access users Creating database accounts for analytical client tools Module 7: Getting Your Dataset to the Client Connecting to SQL Server and Submitting Queries from Client Tools Connecting and running SELECT queries from: Excel PowerBI RStudio Exporting datasets to files using Results pane from SSMS The bcp utility The Import/Export Wizard Additional course details: Nexus Humans Writing Analytical Queries for Business Intelligence 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 Writing Analytical Queries for Business Intelligence 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.

Overview This comprehensive course on Spatial Data Visualization and Machine Learning in Python Level 4 will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Spatial Data Visualization and Machine Learning in Python Level 4 comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? After successfully completing the course you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this Spatial Data Visualization and Machine Learning in Python Level 4. It is available to all students, of all academic backgrounds. Requirements Our Spatial Data Visualization and Machine Learning in Python Level 4 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 8 sections • 21 lectures • 04:40:00 total length •Introduction: 00:14:00 •Python Installation: 00:03:00 •Installing Bokeh: 00:04:00 •Data Preparation: 00:24:00 •Creating a Bar Chart: 00:18:00 •Creating a Line Chart: 00:12:00 •Creating a Doughnut Chart: 00:22:00 •Creating a Magnitude Plot: 00:31:00 •Creating a Geo Map Plot: 00:20:00 •Creating a Grid Plot: 00:12:00 •Data Pre-processing: 00:21:00 •Building a Predictive Model: 00:21:00 •Building a Prediction Dataset: 00:07:00 •Adding predicted data to our plots - Part 1: 00:13:00 •Adding predicted data to our plots - Part 2: 00:14:00 •Adding predicted data to our plots - Part 3: 00:15:00 •Adding the Grid Plot: 00:08:00 •Installing Visual Studio Code: 00:01:00 •Creating the Project and Virtual Environment: 00:08:00 •Building and Running the Server: 00:12:00 •Resources: 00:00:00

Learn Python 3 programming fast!

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