985 Programming Languages courses

Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online. Learn to code a Password Validator in 1 hour. 

Duration 5 Days 30 CPD hours This course is intended for This course is primarily for Developers, Developer Consultants, Help Desk/COE Support, and Program/Project Managers. Overview Learn the fundamental concepts of the ABAP programming languageEfficiently use the ABAP Workbench toolsCreate simple application programs with user dialogs (list, selection screen, screens, Web Dynpro) and database dialogs (reading from the database) In this course, students gain knowledge of the fundamental concepts of ABAP and learn how to comfortably and efficiently work with the ABAP Workbench tools in order to undertake custom developments with confidence. Flow of an ABAP Program Describing the Processing of ABAP Programs ABAP Workbench Introduction Introducing the ABAP Development Environment Organizing ABAP Developments Developing Programs Finalizing Development Basic ABAP Language Elements Defining Elementary Data Objects Using Basic ABAP Statements Working with the ABAP Debugger Modularization Introducing Modularization Modularizing Using Subroutines Modularizing Using Function Modules Implementing Function Modules Modularizing Using BAPIs Modularizing Using Global Classes Implementing Simple Global Classes and Static Methods Modularizing Using Local Classes Complex Data Objects Working with Structures Working with Internal Tables Data Modeling and Data Retrieval Modeling Data Reading Single Database Records Reading Multiple Database Records Handling Other Aspects of Database Access Working with Authorization Checks Classic ABAP Report Implementing ABAP Lists Implementing Selection Screens Implementing Events of ABAP Reports Screen Creating Screens Creating Input/Output Fields Implementing Data Transport SAP List Viewer Using the SAP List Viewer Web Dynpro ABAP Describing Web Dynpro ABAP Implementing Navigation in Web Dynpro Implementing Data Transport in Web Dynpro Program Analysis Tools Using the Code Inspector ABAP Development Tools for SAP NetWeaver Describing ABAP Development Tools for SAP NetWeaver Creating an ABAP Project in Eclipse SAP Standard Software Adjustments Adjusting the SAP Standard Software Additional course details: Nexus Humans BC400 SAP ABAP Workbench Foundations 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 BC400 SAP ABAP Workbench Foundations 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.

In this course, you will learn how to unlock the power of Generative AI and learn to generate passive income for profitable online ventures with ChatGPT. Gain the skills to automate tasks efficiently, generate revenue from your content, and uphold ethical AI practices. This course is perfect for beginners or anyone seeking to enhance their online ventures with AI technology.

Discover how to utilize VBA to automate procedures and effortlessly generate reports with a single button press. Streamline your tasks and achieve seamless productivity by performing various actions at the click of a button. No prior knowledge of VBA is required but familiarity with Excel will be an advantage.

This video course takes you through the basic and advanced concepts of penetration testing. From setting up your own virtual lab to developing brute force attacking tools using Python, you'll learn it all with the help of engaging activities.

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.

Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently

The underlying patterns in your data hold vital insights; unearth them with cutting-edge clustering and classification techniques in R

If you’re looking to start a career in Python coding, but don’t know where to begin, this might be for you. This course is aimed at absolute beginners that have never done any coding before. Early on in the course, you’ll learn what coding is, what certain types of languages are used for, specifically Python, and the types of careers available through learning Python.

Overview This comprehensive course on C++ Complete Coding Course will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This C++ Complete Coding Course 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? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this C++ Complete Coding Course. It is available to all students, of all academic backgrounds. Requirements Our C++ Complete Coding Course 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 Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 14 sections • 79 lectures • 05:33:00 total length •Introduction: 00:04:00 •What Is C++?: 00:03:00 •Setting up A Project: 00:07:00 •Console Out: 00:04:00 •Data Types: 00:03:00 •Variables: 00:04:00 •Console In: 00:03:00 •Strings: 00:04:00 •Constants: 00:05:00 •Assignment Operator: 00:03:00 •Arithmetic Operators: 00:04:00 •Compound Assignment Operator: 00:03:00 •Increment & Decrement Operators: 00:04:00 •Relation & Comparison Operators: 00:06:00 •Logical Operators: 00:07:00 •Conditional Ternary Operator: 00:04:00 •Comma Operator: 00:03:00 •Type Casting Operator: 00:02:00 •Bitwise Operators: 00:12:00 •Size of Operator: 00:03:00 •Operator Precedence: 00:05:00 •String Streams: 00:04:00 •Conditional Statements: 00:07:00 •For Loop: 00:04:00 •While Loop: 00:03:00 •Do While Loop: 00:04:00 •Range-Based For Loop: 00:03:00 •GoTo Statement: 00:04:00 •Switch Statement: 00:05:00 •Functions: 00:03:00 •Function Return Statement: 00:04:00 •Function Arguments Passed By Value: 00:05:00 •Function Arguments Passed By Reference: 00:05:00 •Function Parameter Default Values: 00:03:00 •Overloaded Functions: 00:04:00 •Function Templates: 00:04:00 •Namespaces: 00:06:00 •Arrays: 00:03:00 •Multidimensional Arrays: 00:03:00 •References: 00:02:00 •Pointers: 00:04:00 •Delete Operator: 00:02:00 •Struct: 00:04:00 •Type Aliasing: 00:03:00 •Unions: 00:04:00 •Enumerators: 00:04:00 •Introduction to Classes: 00:05:00 •Class Access: 00:04:00 •Class Constructor: 00:05:00 •Class Pointers: 00:04:00 •Overloading Operators: 00:06:00 •This Keyword: 00:04:00 •Constant Objects: 00:03:00 •Getters and Setters: 00:05:00 •Static Variables: 00:04:00 •Static Functions: 00:06:00 •Template Classes: 00:05:00 •Class Destructor: 00:04:00 •Class Copy Constructor: 00:03:00 •Friend Function: 00:06:00 •Friend Class: 00:06:00 •Class Inheritance: 00:07:00 •Multiple Class Inheritance: 00:05:00 •Virtual Methods: 00:04:00 •Abstract Base Class: 00:03:00 •Error Handling: 00:04:00 •Preprocessor Macro Definitions: 00:04:00 •Preprocessor Conditional Directives: 00:05:00 •Preprocessor Line Directive: 00:04:00 •Preprocessor Error Directive: 00:03:00 •Preprocessor Source File Inclusion: 00:02:00 •Opening A File: 00:06:00 •Writing to a File: 00:04:00 •Commenting: 00:04:00 •Class Header and Implementation: 00:09:00 •Lists: 00:04:00 •Vectors: 00:05:00 •Resource - C++ Complete Coding Course: 00:00:00 •Assignment - C++ Complete Coding Course: 00:00:00