1014 Data Science courses

Maximize the value of data assets in the oil and gas sector with EnergyEdge's assessment-based training course on Python programming and analytics.

Duration 3 Days 18 CPD hours This course is intended for This course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their programming proficiency in Python 3. Overview In this course, you will expand your Python proficiencies. You will: Select an object-oriented programming approach for Python applications. Create object-oriented Python applications. Create a desktop application. Create data-driven applications. Create and secure web service-connected applications. Program Python for data science. Implement unit testing and exception handling. Package an application for distribution. Python© continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, creating web service-connected apps, performing data science tasks, unit testing, and creating and installing packages and executable applications. Lesson 1: Selecting an Object-Oriented Programming Approach for Python Applications Topic A: Implement Object-Oriented Design Topic B: Leverage the Benefits of Object-Oriented Programming Lesson 2: Creating Object-Oriented Python Applications Topic A: Create a Class Topic B: Use Built-in Methods Topic C: Implement the Factory Design Pattern Lesson 3: Creating a Desktop Application Topic A: Design a Graphical User Interface (GUI) Topic B: Create Interactive Applications Lesson 4: Creating Data-Driven Applications Topic A: Connect to Data Topic B: Store, Update, and Delete Data in a Database Lesson 5: Creating and Securing a Web Service-Connected App Topic A: Select a Network Application Protocol Topic B: Create a RESTful Web Service Topic C: Create a Web Service Client Topic D: Secure Connected Applications Lesson 6: Programming Python for Data Science Topic A: Clean Data with Python Topic B: Visualize Data with Python Topic C: Perform Linear Regression with Machine Learning Lesson 7: Implementing Unit Testing and Exception Handling Topic A: Handle Exceptions Topic B: Write a Unit Test Topic C: Execute a Unit Test Lesson 8: Packaging an Application for Distribution Topic A: Create and Install a Package Topic B: Generate Alternative Distribution Files

Duration 3 Days 18 CPD hours This course is intended for This course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their programming proficiency in Python 3. Overview In this course, you will expand your Python proficiencies. You will: Select an object-oriented programming approach for Python applications. Create object-oriented Python applications. Create a desktop application. Create data-driven applications. Create and secure web service-connected applications. Program Python for data science. Implement unit testing and exception handling. Package an application for distribution. Python continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, creating web service-connected apps, performing data science tasks, unit testing, and creating and installing packages and executable applications. Lesson 1: Selecting an Object-Oriented Programming Approach for Python Applications Topic A: Implement Object-Oriented Design Topic B: Leverage the Benefits of Object-Oriented Programming Lesson 2: Creating Object-Oriented Python Applications Topic A: Create a Class Topic B: Use Built-in Methods Topic C: Implement the Factory Design Pattern Lesson 3: Creating a Desktop Application Topic A: Design a Graphical User Interface (GUI) Topic B: Create Interactive Applications Lesson 4: Creating Data-Driven Applications Topic A: Connect to Data Topic B: Store, Update, and Delete Data in a Database Lesson 5: Creating and Securing a Web Service-Connected App Topic A: Select a Network Application Protocol Topic B: Create a RESTful Web Service Topic C: Create a Web Service Client Topic D: Secure Connected Applications Lesson 6: Programming Python for Data Science Topic A: Clean Data with Python Topic B: Visualize Data with Python Topic C: Perform Linear Regression with Machine Learning Lesson 7: Implementing Unit Testing and Exception Handling Topic A: Handle Exceptions Topic B: Write a Unit Test Topic C: Execute a Unit Test Lesson 8: Packaging an Application for Distribution Topic A: Create and Install a Package Topic B: Generate Alternative Distribution Files

This course first equips you with the fundamentals of Python and then progresses to teach you how to use various libraries such as NumPy, Pandas, Seaborn, Bokeh, and so on. This course contains several mini projects so that, by the end of this course, you will be equipped with the essential tools you need to become a visualization expert.

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Here's what you get: Step by step Computer Vision: C++ and OpenCV with GPU support lessons One to one assistance from Computer Vision: C++ and OpenCV with GPU supportprofessionals if you need it Innovative exams to test your knowledge after the Computer Vision: C++ and OpenCV with GPU supportcourse 24/7 customer support should you encounter any hiccups Top-class learning portal Unlimited lifetime access to all twenty-five Computer Vision: C++ and OpenCV with GPU support courses Digital Certificate, Transcript and student ID are all included in the price PDF certificate immediately after passing Original copies of your Computer Vision: C++ and OpenCV with GPU support certificate and transcript on the next working day Easily learn the Computer Vision: C++ and OpenCV with GPU support skills and knowledge you want from the comfort of your home CPD 250 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Computer Vision: C++ and OpenCV with GPU support training is suitable for - Students Recent graduates Job Seekers Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Computer Vision: C++ and OpenCV with GPU support Requirements To participate in this Computer Vision: C++ and OpenCV with GPU support course, all you need is - A smart device A secure internet connection And a keen interest in Computer Vision: C++ and OpenCV with GPU support Career path You will be able to kickstart your Computer Vision: C++ and OpenCV with GPU support career because this course includes various courses as a bonus. This Computer Vision: C++ and OpenCV with GPU support is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Computer Vision: C++ and OpenCV with GPU support career opportunities. 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Take a step toward a brighter future with our Healthcare Assistant course! *** Course Curriculum *** Here is the curriculum breakdown of the Healthcare Assistant at QLS Level 5 course: Working in Different Healthcare Settings Understanding Legal, Professional Standards of Practice and Ethical Aspects of Health Care Part - 1 Understanding Legal, Professional Standards of Practice and Ethical Aspects of Health Care Part - 2 Maintaining Medical Records Confidentiality in a Medical Environment Health and Safety Responsibilities Hygiene in Nursing Infection Control Mobility and Immobility Issues of Patients in Nursing Rights and Responsibilities as a Health and Social Care Worker Role as A Caregiver and Healthcare Professional Providing Care or Treatment to People Who Lack Capacity Managing Service Delivery in Health and Social Care Medical Jargon and Terminology Effects of Covid-19 on Human Life Preventions and Social Measures to Be Taken Information Technology in Health Care Artificial Intelligence, Data Science and Technological Solutions against Covid-19 Assessment Process You have to complete the assignment questions given at the end of the course and score a minimum of 60% to pass each exam. Our expert trainers will assess your assignment and give you feedback after you submit the assignment. You will be entitled to claim a certificate endorsed by the Quality Licence Scheme after you have completed all of the Diploma in Healthcare Assistant at QLS Level 5 exams. CPD 150 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Healthcare Assistant at QLS Level 5 course is perfect for highly motivated people who want to improve their technical skills and prepare for the career they want! Requirements No prior background or expertise is required in this Healthcare Assistant course. Career path This Healthcare Assistant Training will allow you to kickstart or take your career to the next stage in the related sector such as: Healthcare Assistant Community Healthcare Assistant healthcare consultant Healthcare Trainer Medical assistant roles. 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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 After completing this course, students will be able to: - 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 course is about writing TSQL queries for the purpose of database reporting, analysis, and business intelligence. 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 Lab 1: Introduction to TSQL for Business Intelligence 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 Lab 1: Write queries 3 - COMBINING COLUMNS FROM MULTIPLE TABLES INTO A SINGLE DATASET: THE JOIN OPERATORS Primary Keys, Foreign Keys, and Joins Understanding Joins, Part 1: CROSS JOIN and the Full Cartesian Product Understanding Joins, Part 2: The INNER JOIN Understanding Joins, Part 3: The OUTER JOINS Understanding Joins, Part 4: Joining more than two tables Understanding Joins, Part 5: Combining INNER and OUTER JOINs Combining JOIN Operations with WHERE and ORDER BY Lab 1: Write SELECT queries 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 Lab 1: Write queries 5 - SUBQUERIES, DERIVED TABLES AND COMMON TABLE EXPRESSIONS Non-correlated and correlated subqueries Derived tables Common table expressions Lab 1: Write queries 6 - ENCAPSULATING DATA RETRIEVAL LOGIC Views Table-valued functions Stored procedures Creating objects for read-access users Creating database accounts for analytical client tools Lab 1: Encapsulating Data Retrieval Logic 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 Lab 1: Getting Your Dataset to the Client Additional course details: Nexus Humans 55232 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 55232 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.

A course by Sekhar Metla IT Industry Expert RequirementsNo pre-knowledge is required - enthusiasm is all you need!, you will be trained from scratchNo paid software required - all coding will be created with open sourceA PC or Mac computer with access to the internetNo programming experience needed. You will learn everything you need to know Audience Beginners - Those who are new to web development and want to learn both frontend and backend technologies. Frontend Developers looking to expand their skills and venture into backend development to enhance their career opportunities. Backend Developers seeking to gain expertise in frontend technologies to be able to build complete web applications and work on both ends of the development stack. Aspiring Full Stack Developers Individuals who aspire to work as full stack developers and want to gain a comprehensive understanding of the entire web development process. Web Designers - who want to complement their design skills with coding abilities and create fully functional web applications. Software Engineers interested in strengthening their skills and knowledge in full stack development to contribute effectively to end-to-end projects. Computer Science Students studying computer science or related fields who wish to get hands-on experience and practical knowledge in web development. Career Changers Professionals from other industries who want to transition into the field of web development and need a complete understanding of full stack technologies. Who wants to become a Full stack developer curious about full stack development and data science Audience Beginners - Those who are new to web development and want to learn both frontend and backend technologies. Frontend Developers looking to expand their skills and venture into backend development to enhance their career opportunities. Backend Developers seeking to gain expertise in frontend technologies to be able to build complete web applications and work on both ends of the development stack. Aspiring Full Stack Developers Individuals who aspire to work as full stack developers and want to gain a comprehensive understanding of the entire web development process. Web Designers - who want to complement their design skills with coding abilities and create fully functional web applications. Software Engineers interested in strengthening their skills and knowledge in full stack development to contribute effectively to end-to-end projects. Computer Science Students studying computer science or related fields who wish to get hands-on experience and practical knowledge in web development. Career Changers Professionals from other industries who want to transition into the field of web development and need a complete understanding of full stack technologies. Who wants to become a Full stack developer curious about full stack development and data science

This award introduces the critical concepts associated with AI and explores its relationship with the systems and processes that make up the digital ecosystem. It explores how AI can empower organisations to utilise Big Data through the use of Business Analysis and Machine Learning, and encourages candidates to consider a future vision of the world that is powered by AI.

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