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Low-Code AI Application Development
Xcel Learning

Enroll Today: Free Assessment, Free Certificate, Lifetime Access

Summary

Price
£22 inc VAT
Study method
Online, On Demand 
Duration
1.2 hours · Self-paced
Qualification
No formal qualification
Certificates
  • Reed Courses Certificate of Completion - Free
Assessment details
  • Review Questions and Assessments (included in price)
Additional info
  • Tutor is available to students

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Overview

Low-Code AI Application Development equips learners with the knowledge and practical skills to design, build, deploy, and scale intelligent applications using modern low-code platforms. This course bridges the gap between traditional software development and artificial intelligence by enabling participants to integrate machine learning, generative AI, automation, and data-driven decision-making without extensive coding. Learners explore platform architecture, data preparation, model building, workflow orchestration, UI/UX design, API integration, security, governance, and performance optimization. Through hands-on projects and a comprehensive capstone experience, participants gain real-world experience in delivering scalable, secure, and user-centered AI solutions. By the end of the course, learners will be prepared to lead digital transformation initiatives, implement responsible AI practices, and create enterprise-ready applications that combine innovation, efficiency, and strategic impact.

Certificates

Assessment details

Review Questions and Assessments

Included in course price

Curriculum

13
sections
13
lectures
1h 15m
total

Description

Discover the Exciting Topics Awaited in this Enriching Course!

Chapter 1: Introduction to Low-Code and AI Fundamentals

  1. Understanding Low-Code Development Platforms
  2. Overview of Artificial Intelligence Concepts
  3. Differences Between Traditional Coding and Low-Code
  4. AI Use Cases Across Industries
  5. The Future of Low-Code AI Development

Chapter 2: Foundations of AI for Developers

  1. Basics of Machine Learning
  2. Introduction to Deep Learning
  3. Natural Language Processing Fundamentals
  4. Computer Vision Basics
  5. Responsible and Ethical AI Principles

Chapter 3: Low-Code Platform Architecture

  1. Components of Low-Code Platforms
  2. Visual Development Environments
  3. Workflow Automation and Orchestration
  4. Integration with External Services and APIs
  5. Deployment Models (Cloud, Hybrid, On-Premise)

Chapter 4: Data Preparation and Management

  1. Data Collection Strategies
  2. Data Cleaning and Transformation
  3. Working with Structured vs Unstructured Data
  4. Connecting Databases and Data Sources
  5. Data Governance and Security Best Practices

Chapter 5: Building AI Models with Low-Code Tools

  1. Pre-Built AI Models and Templates
  2. Training Custom Models Without Coding
  3. Feature Selection and Engineering in Low-Code
  4. Model Evaluation and Validation
  5. Model Deployment and Versioning

Chapter 6: Automating Workflows with AI

  1. Designing Intelligent Workflows
  2. Event-Driven Automation
  3. Chatbots and Virtual Assistants
  4. Document Processing Automation
  5. Monitoring and Optimization of Automated Processes

Chapter 7: UI/UX Design for AI Applications

  1. Designing User-Centric AI Interfaces
  2. Drag-and-Drop UI Builders
  3. Conversational Interface Design
  4. Accessibility in AI Applications
  5. Prototyping and User Testing

Chapter 8: Integration and API Management

  1. Connecting AI Services via APIs
  2. RESTful and GraphQL Integrations
  3. Authentication and Authorization
  4. Webhooks and Event-Based Integrations
  5. Third-Party AI Service Integration

Chapter 9: Security, Compliance, and Governance

  1. Securing AI Applications
  2. Data Privacy Regulations (GDPR, HIPAA, etc.)
  3. Role-Based Access Control
  4. Audit Trails and Monitoring
  5. Risk Management in AI Systems

Chapter 10: Scaling and Performance Optimization

  1. Performance Monitoring Tools
  2. Scaling AI Applications in the Cloud
  3. Load Balancing Strategies
  4. Cost Optimization Techniques
  5. Continuous Integration and Continuous Deployment (CI/CD)

Chapter 11: Advanced AI Capabilities in Low-Code

  1. Generative AI Integration
  2. Predictive Analytics Applications
  3. Real-Time AI Processing
  4. AI-Powered Recommendation Systems
  5. Custom AI Extensions and Plugins

Chapter 12: Capstone Project and Real-World Applications

  1. Defining the Capstone Project Scope
  2. Designing an End-to-End AI Application
  3. Testing and Quality Assurance
  4. Deployment and User Training
  5. Post-Deployment Maintenance and Iteration

Don't miss out on the chance to discover your full potential. Enroll today and open the door to a world of opportunities. Receive an exclusive digital certificate upon completing the course!

Who is this course for?

This course is designed for developers, business analysts, entrepreneurs, and IT professionals who want to build AI-powered applications without deep coding expertise. It also suits students, product managers, and innovators seeking to rapidly prototype, automate workflows, and integrate AI into solutions using low-code platforms to accelerate digital transformation and productivity.

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Legal information

This course is advertised on Reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.

FAQs

Study method describes the format in which the course will be delivered. At Reed Courses, courses are delivered in a number of ways, including online courses, where the course content can be accessed online remotely, and classroom courses, where courses are delivered in person at a classroom venue.

CPD stands for Continuing Professional Development. If you work in certain professions or for certain companies, your employer may require you to complete a number of CPD hours or points, per year. You can find a range of CPD courses on Reed Courses, many of which can be completed online.

A regulated qualification is delivered by a learning institution which is regulated by a government body. In England, the government body which regulates courses is Ofqual. Ofqual regulated qualifications sit on the Regulated Qualifications Framework (RQF), which can help students understand how different qualifications in different fields compare to each other. The framework also helps students to understand what qualifications they need to progress towards a higher learning goal, such as a university degree or equivalent higher education award.

An endorsed course is a skills based course which has been checked over and approved by an independent awarding body. Endorsed courses are not regulated so do not result in a qualification - however, the student can usually purchase a certificate showing the awarding body's logo if they wish. Certain awarding bodies - such as Quality Licence Scheme and TQUK - have developed endorsement schemes as a way to help students select the best skills based courses for them.
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