Real Work From Real Learners
Our students don't just complete exercises—they build working automation solutions that solve actual business challenges. Browse projects developed during their learning journey, from process streamlining tools to custom reporting dashboards. Each one represents months of hands-on practice with the frameworks and techniques used by automation professionals every day.
Featured Student Projects
These projects showcase what learners accomplish when they combine structured guidance with their own problem-solving instincts. The work you see here was created by people from different backgrounds—some had technical experience, others came from completely unrelated fields.
Invoice Processing Workflow
Automated invoice data extraction and validation system that reduced manual entry time by several hours per week. The system reads incoming PDF invoices, extracts relevant fields, validates against preset rules, and flags exceptions for human review. Built using Python with document parsing libraries.
Customer Feedback Dashboard
An interactive reporting dashboard that aggregates customer feedback from multiple channels into a single view. The tool connects to survey platforms and support ticket systems, categorizes responses, and presents trends over time. Created with database queries and visualization frameworks.
Inventory Alert System
Monitoring tool that tracks inventory levels across multiple locations and sends automated alerts when stock falls below defined thresholds. The system pulls data from existing inventory software, applies business logic, and distributes notifications to relevant team members based on product category and urgency.
Expense Report Generator
Automated monthly expense report compilation from scattered receipt images and spreadsheet data. The workflow collects receipts from designated folders, extracts amounts and dates, matches them with spreadsheet entries, and produces formatted reports ready for accounting review.
Meeting Notes Organizer
System that processes meeting transcripts, identifies action items and deadlines, and distributes summaries to participants. The tool parses text for keywords indicating tasks, extracts responsible parties, and creates trackable items in project management software. Built to reduce post-meeting administrative work.
Lead Response Router
Automated routing system for incoming sales inquiries based on geographic location, product interest, and team capacity. New leads are evaluated against business rules, assigned to appropriate representatives, and logged with initial contact information pre-filled in the CRM system.
Learning With Experienced Guides
Student projects develop through ongoing feedback from professionals who've spent years building automation solutions in real business environments. Our mentors review work, suggest improvements, and share practical insights that only come from hands-on experience. They're here to help learners avoid common pitfalls and develop approaches that actually work when projects move from practice to production.
Iskra Pavlovic
Process Automation Specialist
Spent twelve years designing workflow systems for mid-sized organizations. Now helps students understand how automation decisions affect entire business operations, not just individual tasks. Focuses on teaching maintainable approaches that other team members can understand and modify.
Elina Virtanen
Integration Architecture Consultant
Background in connecting disparate business systems and making them communicate effectively. Guides students through the technical considerations of working with APIs, data formats, and error handling. Known for turning confusing technical documentation into practical implementation steps.
How Projects Actually Develop
Student projects don't appear fully formed. They evolve through repeated cycles of building, testing, getting feedback, and refining. The timeline below shows how a typical project progresses from initial concept to working solution—including the inevitable moments where things don't work as expected and need rethinking.
Problem Identification
Students start by identifying a repetitive task or inefficient process they want to address. This phase involves documenting current steps, understanding pain points, and defining what success looks like. Many discover the actual problem is different from what they initially thought.
Solution Design
With the problem clearly defined, learners map out their approach—which tools they'll use, what data they need to access, and how components will connect. Mentors review these plans and point out potential complications before any code gets written.
Iterative Building
Development happens in small increments. Build one piece, test it, fix what breaks, then move to the next component. This stage usually takes longer than expected because real-world data is messier than practice datasets, and edge cases appear that weren't obvious during planning.
Testing and Refinement
Once the basic functionality works, students stress-test their solution with realistic scenarios. They add error handling for situations they hadn't considered, improve performance for larger data volumes, and make the interface more intuitive based on feedback from potential users.
Documentation and Handoff
Final phase involves documenting how the solution works, creating instructions for anyone who might maintain it later, and preparing deployment materials. This step often reveals gaps in understanding that send students back to clarify their approach before considering the project truly complete.