About Course
SkilBrill's workfusion training goes past simple bot building: 11 weeks on intelligent document processing, ML models and scoring, training data quality and workforce orchestration, so you can run automation programmes that mix bots, rules and human review in the same process.
Course Overview
Who Should Join This Course
- RPA developers moving from pure bot building into intelligent automation
- Business analysts responsible for labelling training data and tuning extraction
- Automation architects designing human-in-the-loop document pipelines
- Operations managers running document-heavy back-office processes
- Consultants implementing WorkFusion in banking, insurance and BPO environments
Prerequisites
- Experience with any RPA tool, or a completed RPA fundamentals course
- Basic statistics: accuracy, precision, recall and what a training set is
- Comfortable with JSON and REST API basics
- Laptop with 16 GB RAM for the WorkFusion trial environment
Learning Objectives
- Design intelligent automation processes that combine RPA, IDP and ML scoring
- Build and evaluate document extraction models with properly sampled training data
- Orchestrate work across bots and humans with workforce orchestration rules
- Tune confidence thresholds so review queues stay small and still accurate
- Integrate WorkFusion with enterprise systems through APIs and connectors
- Defend an automation business case, not just a bot demo, in interviews
66 hrs across 11 modules
Tools and Technologies
WorkFusion Studio, Intelligent Automation Cloud, Control Tower, IDP, ML scoring, Workforce Orchestration, bot agents, work queues
Career Opportunities After This Programme
- Intelligent Automation Developer
- IDP and ML Automation Analyst
- RPA Developer, WorkFusion
- Automation Solution Architect
- Document Processing Consultant
- Automation Programme Analyst
Hands-on Labs
- Hands-on lab on IDP — build an extraction model for invoice forms, publish it and clear low-confidence fields in a review queue with documented acceptance criteria
- Hands-on lab on ML scoring — label a training set, train a model, read precision and recall, then retrain after deliberately skewing the sample data
- Hands-on lab on workforce orchestration — configure rules that split a claims queue between bot processing and human review and measure the effect on turnaround time
- Hands-on lab on process design — build a WorkFusion process that pulls documents from an inbox, classifies them, extracts fields and posts results to a downstream system
- Hands-on lab on exceptions — break a live process on purpose, then work the failure queue until the audit trail is clean again
- Hands-on lab on analytics — build a Control Tower view showing throughput, model accuracy and reviewer backlog for a document process
Career Roadmap
Role Progression
- RPA Developer
- Intelligent Automation Developer
- IDP and ML Automation Analyst
- Automation Solution Architect
- Intelligent Automation Programme Lead
Step-by-Step Learning Path
- Master the platform foundations
- Build automations or applications end to end
- Learn administration, security and integrations
- Complete the capstone project
- Prepare for technical interviews and update your resume and portfolio
Course Duration, Mode and Certification
The course runs for 11 weeks with 3 sessions per week (2 hours per session), totalling 66 classroom hours. Classroom, online, and hybrid modes are available where supported. You will receive a SkilBrill completion certificate and work on real-world projects, with dedicated interview preparation support at the end of the programme.
Why Train at SkilBrill
SkilBrill Training Institute focuses on making you employable. Trainers are working professionals, labs mirror real production environments, and the placement cell connects eligible candidates with hiring companies. Enquire today for the next batch start date and fee details.
Career and Job Support
SkilBrill provides practical career support to help you move from training into relevant roles. Services include:
- Resume assistance
- LinkedIn profile guidance
- Portfolio guidance
- Technical interview preparation
- Mock interviews
- Project explanation preparation
- Job-search guidance
- Placement assistance
Resume Building Guidance
- Keep your resume to one page if you have less than five years of experience.
- Use a clean format with clear sections: contact, objective, skills, projects, education and certifications.
- Tailor your skills section to match the job description.
- Quantify achievements where possible, for example "cut manual reconciliation from four hours to twenty minutes".
- Include links to your GitHub, LinkedIn and portfolio if available.
- Proofread carefully; spelling and grammar errors create a poor impression.
LinkedIn Profile Optimisation
- Use a professional headshot and a headline that includes your target role.
- Write a summary that highlights your skills, projects and career goals.
- List relevant tools, frameworks and certifications in the Skills section.
- Share posts or articles about what you are learning to show activity.
- Connect with trainers, classmates and professionals in your target domain.
- Request recommendations from mentors or project reviewers.
GitHub and Portfolio Guidance
- Create well-named repositories for each major project.
- Add a README file explaining the project, technologies, setup steps and screenshots.
- Use meaningful commit messages and keep code organised.
- Include a portfolio website or GitHub profile readme that links to your best work.
- Keep sensitive data like passwords and API keys out of public repositories.
- Regularly update repositories with improvements and new projects.
Job Search Strategy
- Update your resume and LinkedIn profile before applying.
- Apply to roles on LinkedIn, Naukri, Indeed and company career pages.
- Customise each application to match the job description.
- Prepare a short elevator pitch for phone screenings.
- Practise technical and behavioural questions daily.
- Follow up politely after interviews and ask for feedback.
- Attend meetups, webinars and networking events in your domain.
Frequently Asked Questions
What is WorkFusion used for?
WorkFusion builds intelligent automation. It combines RPA bots, document extraction and machine learning scoring to automate processes that involve unstructured documents, not just rule-based clicks.
What is the difference between WorkFusion and UiPath?
UiPath starts from robotic process automation and adds AI through AI Center. WorkFusion starts from document and ML processing and adds bots, so it tends to suit document-heavy operations such as claims and onboarding.
Do I need machine learning knowledge for workfusion training?
You do not need to write models from scratch. You do need to understand training data, confidence scores, precision and recall, because tuning extraction quality is a large part of the job.
What is workforce orchestration in WorkFusion?
It is the layer that decides how each work item gets done: which bot handles it, which queue it lands in, when a human reviewer steps in, and what service level applies to it.
How long does workfusion training take?
Eleven weeks at six hours a week. It moves faster if you already know an RPA tool, since most of the new material is IDP, ML evaluation and orchestration.
What roles suit someone with WorkFusion skills?
Intelligent automation developer, IDP or automation analyst, document processing consultant and automation solution architect. Roles cluster in banking, insurance, BPO and shared services.