730 Software Development courses delivered Live Online

Duration 2 Days 12 CPD hours This course is intended for This course is intended for software testers, architects, engineers, or other related roles, who wish to apply AI to software testing practices within their enterprise. While there are no specific pre-requisites for this course, it would be helpful is the attendee has familiarity with basic scripting (Python preferred) and be comfortable with working from the command line (for courses that add the optional hands-on labs). Attendees without basic scripting skills can follow along with the hands-on labs or demos. Overview This course introduces AI and related technologies from a practical applied software testing perspective. Through engaging lecture and demonstrations presented by our expert facilitator, students will explore: Exploring AI Introduction to Machine Learning Introduction to Deep Learning Introduction to Data Science Artificial Intelligence (AI) in Software Testing Implementing AI in Test Automation Innovative AI Test Automation Tools for the Future Implementing AI in Software Testing / AI in Test Automation is an introductory-level course for attendees new to AI, Machine Learning or Deep Learning who wish to automate software testing tasks leveraging AI. The course explores the essentials of AI, ML and DL and how the integrate into IT business operations and initiatives. Then the course moves to specifics about the skills, techniques and tools used to apply AI to common software testing requirements. Exploring AI AI-Initiatives The Priority: Excellence AI- Intelligence Types The Machine Learning Types The Quality Learning Initiative The Inception in Academics AI - Importance & Applications The Re-visit Learning Re-visited via AI Teaching in the world of AI Exploring AI for Self-Development AI In Academics Beyond Academics Introduction to Machine Learning What is Machine Learning? Why Machine Learning? Examples - Algorithms behind Machine Learning Introduction to Deep Learning What is Deep Learning? Why Deep Learning? Example - Deep Learning Vs Machine Learning Introduction to Data Science What is Data Science? Why Data Science? Examples - Use Cases of Data Science Artificial Intelligence (AI) in Software Testing What is AI in Software Testing? The Role of AI Testing Why do we Need AI in Software Testing? Pros and Cons of AI in Software Testing Applications of AI in Software Testing Is it time for Testers or QA Teams to worry about AI? Automated Testing with Artificial Intelligence Implementing AI in Test Automation Training the AI Bots Challenges with AI-powered Applications Examples - Real World use cases using Artificial Intelligence Demo - Facial Emotion Detection Using Artificial Intelligence Demo - Text Analysis API Using Artificial Intelligence Demo - EYE SPY Mobile App Using Artificial Intelligence Innovative AI Test Automation Tools for the Future Tools used for Implementing AI in Automation Testing What is NEXT? AI Test Automation Demo using Testim

Duration 4 Days 24 CPD hours This course is intended for This is an intermediate -level programming course, designed for experienced Java developers who wish to get up and running on developing well defended software applications. Familiarity with Java and JEE is required and real world programming experience is highly recommended. Ideally students should have approximately 6 months to a year of Java and JEE working knowledge. Overview Students who attend Attacking and Securing Java Web Applications will leave the course armed with the skills required to recognize actual and potential software vulnerabilities and implement defenses for those vulnerabilities. This course begins by developing the skills required to fingerprint a web application and then scan it for vulnerabilities and bugs. Practical labs using current tools and techniques provide students with the experience needed to begin testing their own applications. Students also gain a deeper understanding of how attackers probe applications to understand the runtime environment as well as find potential weaknesses. This course the introduces developers to the most common security vulnerabilities faced by web applications today. Each vulnerability is examined from a Java/JEE perspective through a process of describing the threat and attack mechanisms, recognizing associated vulnerabilities, and, finally, designing, implementing, and testing effective defenses. Practical labs reinforce these concepts with real vulnerabilities and attacks. Students are then challenged to design and implement the layered defenses they will need in defending their own applications. There is an emphasis on the underlying vulnerability patterns since the technologies, use cases, and methods of attack as constantly changing. The patterns remain the same through all the change and flux. This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in secure web application development, coding and design, coupling the most current, effective techniques with the soundest industry practices. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. This lab-intensive course provides hands-on Java / JEE security training that offers a unique look at Java application security. Beginning with penetration testing and hunting for bugs in Java web applications, you embrace best practices for defensively coding web applications, covering all the OWASP Top Ten as well as several additional prominent vulnerabilities. You will repeatedly attack and then defend various assets associated with fully functional web applications and services, allowing you to experience the mechanics of how to secure JEE web applications in the most practical of terms. Bug Hunting Foundation Why Hunt Bugs? Safe and Appropriate Bug Hunting/Hacking Scanning Web Applications Scanning Applications Overview Moving Forward from Hunting Bugs Removing Bugs Foundation for Securing Applications Principles of Information Security Bug Stomping 101 Unvalidated Data Broken Authentication Sensitive Data Exposure XML External Entities (XXE) Broken Access Control Bug Stomping 102 Security Misconfiguration Cross Site Scripting (XSS) Deserialization/Vulnerable Components Insufficient Logging and Monitoring Spoofing, CSRF, and Redirects Moving Forward with Application Security Applications: What Next? Making Application Security Real

Duration 3 Days 18 CPD hours This course is intended for Project team members and Key-Users responsible for the maintenance of Execution Steps for process orders and production orders to generate interactive PI Sheets and work instructions for operators and workers in the production plant and to realize the data exchange with the automation and process control world. In this course, students will attain the ability to maintain Execution Steps for process orders and production orders to generate interactive PI sheets and work instructions. Course Outline Process management / process integration Control recipes / control instructions XSteps Process messages Customizing

Duration 3.5 Days 21 CPD hours This course is intended for This course is aimed at students new to the language who may or may not have experience with other programming languages. Overview Learn how Python works and what it's good for. Understand Python's place in the world of programming languages Learn to work with and manipulate strings in Python. Learn to perform math operations with Python. Learn to work with Python sequences: lists, arrays, dictionaries, and sets. Learn to collect user input and output results. Learn flow control processing in Python. Learn to write to and read from files using Python. Learn to write functions in Python. Learn to handle exceptions in Python. Learn to work with dates and times in Python. In this Python training course by Webucator, Inc, students learn to program in Python. Python Basics Running Python Hello, World! Literals Python Comments Data Types Variables Writing a Python Module print() Function Named Arguments Collecting User Input Getting Help Functions and Modules Defining Functions Variable Scope Global Variables Function Parameters Returning Values Importing Modules Math Arithmetic Operators Modulus and Floor Division Assignment Operators Built-in Math Functions The math Module The random Module Seeding Python Strings Quotation Marks and Special Characters String Indexing Slicing Strings Concatenation and Repetition Common String Methods String Formatting Built-in String Functions Iterables: Sequences, Dictionaries, and Sets Definitions Sequences Unpacking Sequences Dictionaries The len() Function Sets *args and **kwargs Flow Control Conditional Statements The is and is not Operators Python's Ternary Operator Loops in Python The enumerate() Function Generators List Comprehensions File Processing Opening Files The os and os.path Modules Exception Handling Wildcard except Clauses Getting Information on Exceptions The else Clause The finally Clause Using Exceptions for Flow Control Exception Hierarchy Dates and Times Understanding Time The time Module The datetime Module Running Python Scripts from the Command Line The sys Module sys.argv

Duration 2 Days 12 CPD hours This course is intended for This course is aimed at anyone currently working with data who is interested in using data visualisation to more effectively communicate their results. Overview At completion, delegates will understand how data visualisations can be best used to communicate actionable insights from data and be competent with the tools required to do it. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations from data. Course Outline The use of analytics, statistics and data science in business has grown massively in recent years. Harnessing the power of data is opening actionable insights in diverse industries from banking to horse breeding. The companies doing this most successfully understand that using sophisticated analytics approaches to unlock insights from data is only half the job. Communicating these insights to all of the different parts of an organisation is just as important as doing the actual analysis. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations from data. To attend this course delegates should be competent in the use of data analysis tools such as reporting tools, spreadsheet software or business intelligence tools. The course will explore the following topics through a series of interactive workshop sessions: Fundamentals of data visualisation Data characteristics & dimensions Mapping visual encodings to data dimensions Colour theory Graphical perception & communication Interaction design Visualisation different characteristics of data: trends, comparisons, correlations, maps, networks, hierarchies, text Designing effective dashboards

Duration 1 Days 6 CPD hours This course is intended for This basic course is for users and developers familiar with earlier versions of IBM InfoSphere Information Server or IBM InfoSphere MDM who want to learn about new features in V11.3 Overview The objectives of this course are as follows:- Learn about the new features of DataStage V11.3- Learn about the new features of Information Analyzer V11.3- Learn about the new features of Data Click V11.3- Learn about the new features of the Information Governance Catalog V11.3 This course is designed to introduce you to new features in data integration and governance in IBM InfoSphere Information Server V11.3 and IBM InfoSphere MDM V11.3. Outline Unit DS: New Features in IBM InfoSphere DataStage V11.3 Unit DC: New Features in IBM InfoSphere Data Click V11.3 Unit IA: New Features in IBM InfoSphere Information Analyzer V11.3 **All units are accompanied by hands-on lab exercises. Additional course details: Nexus Humans KM650 IBM What is New in IBM InfoSphere Data Integration and Governance? V11.3 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 KM650 IBM What is New in IBM InfoSphere Data Integration and Governance? V11.3 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.

Duration 3 Days 18 CPD hours This course is intended for Application ConsultantChange ManagerProgram/Project ManagerSolution ArchitectTechnology Consultant This course will prepare you to understand the Big Picture of Test Management with SAP Solution Manager Test Suite, setup up the Test Environment, use the SAP Solution Manager Test Suite, use advanced functions for Business Process Change Analysis, test Automation, and Scope and Effort Analysis. This course will prepare you to understand the Big Picture of Test Management with SAP Solution Manager Test Suite, setup up the Test Environment, use the SAP Solution Manager Test Suite, use advanced functions for Business Process Change Analysis, test Automation, and Scope and Effort Analysis.

Duration 3 Days 18 CPD hours Discover and explore how to use the fundamental building blocks of the Swift programming language. class will teach you the basic concepts of Swift programming, including syntax, logic, structures, functions, and patterns. It also includes detailed explanations of language syntax and coding exercises. Introduction to Swift Constants, Variables, and Data TypesOperatorsControl FlowStrings & FunctionsStructures & ClassesOptionalsCollectionsLoopsType CastingGuard StatementsScope & EnumerationsProtocolsClosuresExtensions

Duration 3 Days 18 CPD hours This course is intended for This is an introductory level SQL course, appropriate for anyone needing to interface with an Oracle database or those needing a general understanding of Oracle database functionality. That would include end users, business analysts, application developers and database administrators. Overview Working in a hands on learning environment led by our expert practitioner, attendees will explore: Basic RDBMS Principles The SQL Language and Tools Using SQL Developer SQL Query Basics WHERE and ORDER BY Functions ANSI 92 Joins ANSI 99 Joins Subqueries Regular Expressions Analytics A company?s success hinges on responsible, accurate database management. Organizations rely on highly available data to complete all sorts of tasks, from creating marketing reports and invoicing customers to setting financial goals. Data professionals like analysts, developers and architects are tasked with creating, optimizing, managing and analyzing data from databases ? with little room for error. When databases aren?t built or maintained correctly, it?s easy to mishandle or lose valuable data. Our SQL Programming and Database Training Series provides students with the skills they require to develop, analyze and maintain data and in correctly structured, modern and secure databases. A full presentation of the basics of relational databases and their use are also covered. Basic RDBMS Principles Relational design principles Accessing data through a structured query language Entity relationship diagrams Data Domains Null values Indexes Views Denormalization Data Model Review The SQL Language and Tools Using SQL*Plus Why Use SQL*Plus When Other Tools Are Available? Starting SQL*Plus EZConnect SQL Commands PL/SQL Commands SQL*Plus Commands The COLUMN Command The HEADING Clause The FORMAT Clause The NOPRINT Clause The NULL Clause The CLEAR Clause Predefined define variables LOGIN.SQL Command history Copy and paste in SQL*Plus Entering SQL commands Entering PL/SQL commands Entering SQL*Plus commands Default output from SQL*Plus Entering Queries What about PL/SQL? Using SQL Developer Choosing a SQL Developer version Configuring connections Creating A Basic Connection Creating A TNS Connection Connecting Configuring preferences Using SQL Developer The Columns Tab The Data Tab The Constraints Tab The Grants Tab The Statistics Tab Other Tabs Queries In SQL Developer Query Builder Accessing Objects Owned By Other Users The Actions Pulldown Menu Differences between SQL Developer and SQL*Plus Reporting Commands Missing In SQL Developer General Commands Missing In SQL Developer Data Dictionary report User Defined reports Using scripts in SQL Developer WHERE and ORDER BY WHERE clause basics Comparison operators Literals and Constants in SQL Simple pattern matching Logical operations The DUAL table Arithmetic operations Expressions in SQL Character operators Pseudo columns Order by clause basics Ordering Nulls Accent and case sensitive sorts Sampling data WHERE and ORDER BY in SQL Developer All, Any, Some Functions The basics of Oracle functions Number functions Character functions Date functions Conversion functions Other functions Large object functions Error functions The RR format mode; Leveraging your knowledge ANSI 92 JOINS Basics of ANSI 92 Joins Using Query Builder with multiple tables Table Aliases Outer joins Outer Joins In Query Builder Set operators Self-referential joins Non-Equijoins ANSI 99 Joins Changes with ANSI99 CROSS Join NATURAL Join JOIN USING JOIN ON LEFT / RIGHT OUTER JOIN FULL OUTER JOIN Subqueries Why use subqueries? WHERE clause subqueries FROM clause subqueries HAVING clause subqueries CORRELATED subqueries SCALAR subqueries DML and subqueries EXISTS subqueries Hierarchical queries TOP N AND BOTTOM N queries Creating subqueries using Query Builder Regular Expressions Available Regular Expressions Regular Expression Operators Character Classes Pattern matching options REGEX_LIKE REGEXP_SUBSTR REGEXP_INSTR REGEXP_REPLACE REGEXP_COUNT Analytics The WITH clause Reporting aggregate functions Analytical functions User-Defined bucket histograms The MODEL clause PIVOT and UNPIVOT Temporal validity More Analytics RANKING functions RANK DENSE_RANK CUME_DIST PERCENT_RANK ROW_NUMBER Windowing aggregate functions RATIO_TO_REPORT LAG / LEAD Linear Regression functions Inverse Percentile functions Hypothetical ranking functions Pattern Matching Additional course details: Nexus Humans Introduction to SQL Programming Basics (TTSQL002) 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 Introduction to SQL Programming Basics (TTSQL002) 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.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice