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This course equips learners with a comprehensive understanding of the NumPy stack, including NumPy, Matplotlib, Pandas, and SciPy, to effectively tackle common challenges in deep learning and data science. Master the basics with this carefully structured course.

This course focuses on understanding all the basic theory and programming skills required as a data scientist, featuring 35+ practical case studies covering common business problems faced by them. This course seeks to fill all those gaps in knowledge that scare off beginners and simultaneously apply your knowledge of data science and deep learning to real-world business problems.

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Overview This comprehensive course on Computer Science: Graph Theory Algorithms will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Computer Science: Graph Theory Algorithms comes with accredited certification, 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 Computer Science: Graph Theory Algorithms. It is available to all students, of all academic backgrounds. Requirements Our Computer Science: Graph Theory Algorithms 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 17 sections • 44 lectures • 08:37:00 total length •Promo: 00:03:00 •Introduction: 00:14:00 •Common Problem: 00:10:00 •Depth First Search: 00:11:00 •Breadth First Search: 00:08:00 •Breadth First Search Shortest Path on a Grid: 00:17:00 •Storage and Representation of Trees: 00:10:00 •Beginner Tree Algorithms: 00:10:00 •Rooting Tree: 00:05:00 •Center(s) of a Tree: 00:06:00 •Isomorphisms in Trees: 00:11:00 •Isomorphisms in Trees Source Code: 00:10:00 •Lowest Common Ancestor: 00:17:00 •Topological Sort: 00:14:00 •Shortest and Longest Paths on DAGs: 00:10:00 •Khan's Algorithm: 00:13:00 •Dijkstra's Shortest Path Algorithm: 00:25:00 •Dijkstra's Shortest Path Algorithm Source Code: 00:09:00 •Bellman-Ford Algorithm: 00:15:00 •Floyd-Warshall Algorithm: 00:16:00 •Floyd-Warshall Algorithm Source Code: 00:09:00 •Algorithm to Find Bridges and Articulation Points: 00:20:00 •Algorithm to Find Bridges and Articulation Points Source Code: 00:09:00 •Tarjan's Algorithm for Finding Strongly Connected Components: 00:17:00 •Tarjan's Algorithm for Finding Strongly Connected Components Source Code: 00:07:00 •Travelling Salesman Problem (TSP) with Dynamic Programming: 00:21:00 •Travelling Salesman Problem (TSP) with Dynamic Programming Source Code: 00:14:00 •Existence of Eulerian Paths and Circuit: 00:10:00 •Finding Eulerian Paths and Circuits: 00:16:00 •Eulerian Paths Source Code: 00:08:00 •Prim's Minimum Spanning Tree Algorithm (Lazy Version): 00:15:00 •Prim's Minimum Spanning Tree Algorithm ( Eager Version): 00:15:00 •Prim's Minimum Spanning Tree Algorithm Source Code ( Eager Version): 00:09:00 •Max Flow Ford-Fulkerson Method: 00:13:00 •Max Flow Ford-Fulkerson Method Source Code: 00:17:00 •Network Flow: Unweighted Bipartite Graph Matching: 00:11:00 •Network Flow: Mice and Owls: 00:08:00 •Network Flow: Elementary Math: 00:11:00 •Network Flow: Edmond-Karp Algorithm: 00:06:00 •Network Flow: Edmond-Karp Algorithm Source Code: 00:10:00 •Network Flow: Capacity Scaling: 00:10:00 •Network Flow: Capacity Scaling Source Code: 00:06:00 •Network Flow: Dinic's Algorithm: 00:12:00 •Network Flow: Dinic's Algorithm Source Code: 00:09:00

The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Complete Python Machine Learning & Data Science Fundamentals there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Complete Python Machine Learning & Data Science Fundamentals course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00

Duration 1 Days 6 CPD hours This course is intended for This course is designed for skilled users of Microsoft Windows and Office who do not have prior coding or programming experience and who are interested in creating custom business apps quickly and without writing application code. Overview In this course, you will use Microsoft Power Apps to build and deploy low-code business apps. You will: Determine how Microsoft Power Apps can meet your business needs. Plan and design apps. Build canvas apps. Build model-driven apps. Test and deploy apps. This course introduces building low-code/no-code apps with Microsoft© Power Apps©. Most out-of-the-box solutions do not meet exact business needs or integrate well with existing business apps. Power Apps eases users into app development with templates, automated app-building tools, and a streamlined programming language to enable any business user to create a custom app. Getting Started with Microsoft Power Apps Topic A: Introduction to Microsoft Power Platform Topic B: Introduction to Power Apps Topic C: Select App Types to Address Business Needs Planning and Designing Apps Topic A: Plan Apps Topic B: Design Apps Building Canvas Apps Topic A: Create an App from a Blank Canvas Topic B: Create an App from a Template Building Model-Driven Apps Topic A: Create Model-Driven Apps Topic B: Add Visualizations and Reports Testing and Deploying Apps Topic A: Make Apps Available to Other Users Topic B: Test Apps Topic C: Revise Apps

Start your career as an IT Support Engineer and earn up to £34,000 per month. Are you looking to get a job in the rewarding field of IT? Do you want to earn a lot of money monthly by spending less? Our IT Support Job Ready Program is here to make that possible! It is your ultimate gateway to learning IT skills and launching a successful career in this ever-evolving industry. With our comprehensive career bundle, we don't just educate you; we guide you every step of the way until you land that dream job. This exclusive IT Support Job Ready program includes an expertly made collection of courses, each designed to build your expertise from the ground up. Our mission is simple - to be your trusted partner every step of the way, from Training to Employment. In addition to teaching you the technical skills you need, we will also provide you with career mentoring and support. We will help you build your resume, prepare for interviews, and land your dream job. We also have partnerships with many companies that are hiring IT professionals, so we can help you get the job you want. If you are not happy with our service, we also offer a 100% money-back guarantee. With us, you have nothing to risk and everything to gain. So what are you waiting for? Enrol in our IT Support Job Ready Program today and start your journey to becoming a successful IT professional! If you have any questions, you can contact us. We will be happy to provide you with all the information you need. Who Choose Us? So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our IT Support Technician Job Ready Program: Personalised Guidance: Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some experience, we will guide you towards honing your skills and developing a strong foundation in Business Analysis. One-On-One Consultation Sessions with Experts: Gain invaluable insights and guidance from seasoned professionals who have thrived in the IT Support field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise. Extensive Job Opportunities: We have established partnerships with numerous companies actively seeking IT Support Technicians. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere. Our aim is to maximise your employment prospects and provide you with a range of exciting opportunities to choose from. Interview Preparation: We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress. Money-Back Guarantee: Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a 100% money-back guarantee. Continuous Career Support: Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance. Whether you need advice on career advancement, assistance with new projects, or simply a friendly ear to share your achievements, we'll be your trusted partner for long-term success. Courses we will provide once you enrol in the program: Course 01: Windows 10 Pro Complete Training Course 02: Learning Computers and Internet Course 03: Encryption Course 04: Internet of Things Course 05: Cloud Computing / CompTIA Cloud+ (CV0-002) Course 06: Secure Programming of Web Applications Course 07: Building Your Own Computer Course 08: Cloud Computing Training Course 09: Data Center Training Essentials: General Introduction Course 10: Cisco ASA Firewall Training Course 11: ICT: Information and Communication Technology Course 12: Success- The 7 Skills To Success, Confidence & Achievement Course 13: IT Helpdesk Support Essentials Course 14: Functional Skills IT The IT Support Job Ready Program with Career Support & Money Back Guarantee is completed in 9 easy steps: Step 1: Enrol in the Programme Join our ENTRY LEVEL IT Support Training for lifetime access to 14 IT Network Infrastructure courses, complete with secure registration and a 14-day money-back guarantee. Step 2: Initial One-On-One Counselling Session After enroling in the IT Support Training, connect with a career mentor in an initial session to tailor your learning path based on your career goals and skills. Step 3: Certification upon Course Completion After learning from the IT Support courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. These certificates will prove that you're an expert in the subject. Step 4: CV Revamping We'll professionally enhance your CV and LinkedIn profile to effectively showcase your skills in IT Support for the IT/Web industry. Step 5: Building Network and Submitting CV We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your IT Support career goals, including high-profile connections on LinkedIn. Step 6: Interview Preparation: Access our IT Support Training interview question database and practice with simulated interviews for feedback and improvement. Step 7: Securing Job Interviews Leveraging our partnerships with leading companies, we'll secure IT Support job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want. Step 8 Post-Interview Support: We'll provide a debriefing session to reflect on your performance and identify areas of improvement for future IT Support interviews if necessary. Step 9 Job Celebration and Ongoing Support: Once you've secured your dream job in ENTRY LEVEL IT Support Engineer, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role. CPD 100 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This IT Support Job Ready Program is perfect for: Aspiring IT professionals eager to enter the tech industry. Career changers looking to transition into IT support. Recent graduates aiming to enhance their employability in IT. Self-taught tech enthusiasts seeking formal training and certification. Anyone needing structured guidance and support to secure an IT job. Requirements No experience is required. Just enrol & start learning. Career path After completing this IT Support Job Ready Program, you will be able to get different jobs such as: IT Support Technician: £20,000 - £40,000 Network Administrator: £25,000 - £50,000 Cybersecurity Analyst: £30,000 - £75,000 Cloud Computing Specialist: £35,000 - £80,000 Data Center Technician: £25,000 - £65,000 Systems Administrator: £30,000 - £70,000 IT Project Manager: £40,000 - £100,000 Certificates CPD Accredited e-Certificate Digital certificate - Included CPD Accredited Framed (Hardcopy) Certificate Hard copy certificate - Included Enrolment Letter Digital certificate - Included QLS Endorsed Hard Copy Certificate Hard copy certificate - Included Student ID Card Digital certificate - Included

Develop a blockchain notary office on Ethereum and learn all about Solidity, Remix, Ganache, Geth, Metamask, and Truffle

You will not only learn a few lines of code in this course but will also understand the principles of programming. Learn the fundamentals of JavaScript with the latest JavaScript versions (ES6/ES7/ES8/ES9/ES10/ESNext) and you will be well on your way to being a Grandmaster programmer in any language.

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course are Business Process Architects, Developers, Developer Consultants, System Administrators, System Architects, and Technology Consultants. Overview The participants will learn to configure scenariosUnderstand and configure the different options with which a back-end system can be connected to the SAP Process Integration (formerly known as SAP Exchange Infrastructure). In this course, students gain knowledge in configuring SAP Process Integration and learn how to implement different integration scenarios with SAP and non-SAP applications. SAP Process Integration Architecture Describing SAP Process Integration Architecture Explaining the Functionality and Utilization of SAP Process Integration The System Landscape Directory (SLD) Maintaining Products and Software Components in the System Landscape Directory (SLD) Implementing Technical Systems in the System Landscape Directory Maintaining Business Systems for Use in the Integration Directory Interface Objects in the Enterprise Service Repository (ESR) Listing Options for Navigating the Enterprise Services Repository (ESR) Analyzing Interface Objects in the Enterprise Services Repository (ESR) Maintaining Interface Objects Defining Message Processing Types and Quality of Services Object Mapping in the Enterprise Service Repository (ESR) Creating Message Mapping Objects Mapping Between Service Interfaces Analyzing Asynchronous Integration Scenarios Configuration of Integration Directory Communication Objects Using Configuration Views Creating Communication Channels in the Integration Directory (ID) Configuration of Integration Directory Objects for ABAP Processing Analyzing Objects Used in the Configuration of Integration Engine (IE) Communication Analyzing Routing Objects Used in Integration Engine (IE) Communication Analyzing Multiple Receiver Objects Used in Integration Engine (IE) Communication Configuration of Integration Directory Objects for Java Processing Maintaining Objects for Advanced Adapter Engine (AAE)-Only Processing Maintaining Objects for Advanced Adapter Engine Extended (AEX) Message Processing Creating and Deploying Integration Flows to the Advanced Adapter Engine Extended (AEX) Operations of SAP Process Integration Using the Runtime Workbench Using the Process Integration Monitoring (PIMon) Home Using the SAP NetWeaver Administrator Connectivity Options for SAP Process Integration Analyzing Connectivity Options between Back-End Systems with SAP Process Integration HTTP Connectivity Options Configuring the Simple Object Access Protocol (SOAP) Adapter Using Proxy Technology Checking the HTTP ABAP Adapter Using the HTTP_AAE (Java) Adapter File Adapter Configuration Configuring the Receiver File Adapter Configuring a Sender File Adapter Intermediate Document (IDoc) Connectivity Options Using the Intermediate Document (IDoc) Adapter with the Receiver Intermediate Document Adapter for the ABAP Stack Using the Sender Intermediate Document (IDoc) Adapter Using the Intermediate Document (IDoc) Adapter in the Advanced Adapter Engine (AAE) Configuring a Complete Intermediate Document (IDoc) Scenario Configuration of SAP Business Application Programming Interfaces (BAPIs) Connectivity Configuring the Receiver Remote Function Call (RFC) Adapter Configuring the Sender Remote Function Call (RFC) Scenario Enterprise Services and B2B Connectivity Analyzing Enterprise Services Configuring Business-to-Business (B2B) Connectivity Cross-Component Business Process Management (ccBPM) Integration Processes Analyzing the Runtime of the Cross-Component Business Process Management (ccBPM) Identifying the Steps to Create and Use an Integration Process Additional course details: Nexus Humans BIT400 SAP Process Integration 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 BIT400 SAP Process Integration 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.