Investment automation isn't magic — it's methodology
Stop chasing quick returns. Learn how disciplined automation reshapes portfolio management through proven technical frameworks and realistic growth expectations.
What most courses won't tell you about algorithmic investing
After working with over 200 students since 2022, I've noticed something. People arrive expecting automated wealth. They leave understanding automated discipline.
Markets don't reward shortcuts
Automation amplifies your strategy — good or bad. We spend three months teaching you how to build strategies worth automating. That includes understanding when NOT to automate, which might be the most valuable lesson.
Technical skills are baseline, not breakthrough
Python, API integration, backtesting frameworks — you'll learn all of it. But technical execution without market understanding is like having a fast car with no map. We teach both the vehicle and the navigation.
Results develop gradually
Our most successful graduates took 8-14 months to see consistent portfolio improvements. Not because the methods are slow, but because proper implementation requires testing, adjustment, and patience. We're transparent about timelines.
How we actually teach this
No hype, no promises of overnight success. Just a structured path from foundational concepts to practical implementation.
Market fundamentals first
Before touching code, you'll understand market mechanics, risk parameters, and why certain automation strategies exist. Technical tools serve strategy, never the reverse.
Hands-on system building
You'll construct three complete automation systems during the program. Real APIs, actual market data, functional backtesting. Each project addresses different investment approaches and risk profiles.
Portfolio testing cycles
Theory breaks in live conditions. We run supervised testing periods where you deploy strategies in controlled environments, analyze outcomes, and adjust methodologies based on real performance data.
Your progression through the program
Most students complete this sequence in 16-20 weeks, though pace varies based on prior experience and available study time. Each phase builds directly on previous work.
Foundation Phase
Weeks 1-5 establish your technical baseline. Python essentials, data handling, API integration, and basic algorithm logic. You'll write your first automated trade execution script by week four.
- Functional Python proficiency for financial applications
- API connection and data retrieval capabilities
- Basic backtesting framework understanding
Strategy Development
Weeks 6-11 focus on investment logic. You'll study momentum strategies, mean reversion approaches, and risk management frameworks. Each concept gets tested through hands-on strategy construction.
- Three complete strategy implementations
- Risk parameter configuration skills
- Portfolio optimization techniques
Testing & Refinement
Weeks 12-16 move into validation. Your strategies face historical data testing, walk-forward analysis, and supervised live market exposure. Most students discover crucial adjustments during this phase.
- Comprehensive backtesting results analysis
- Strategy adjustment based on live conditions
- Performance tracking and reporting systems
Portfolio Integration
Weeks 17-20 prepare you for independent operation. You'll build monitoring systems, establish maintenance routines, and develop contingency protocols. Graduation requires demonstrating a fully operational automated portfolio system.
- Complete portfolio automation infrastructure
- Monitoring and alert systems
- Documented operational procedures
I came in thinking automation meant passive income. The reality is better — it means disciplined execution without emotional interference. My portfolio shows consistent growth patterns I couldn't achieve with manual trading.
Henrik Bjornstad
Program Graduate, February 2025
Program investment options
All programs include lifetime access to course materials, community forum, and quarterly curriculum updates. First session for all tiers begins March 2026.
Independent Study
One-time payment
- Complete video curriculum access
- Code repositories and templates
- Community forum participation
- Monthly group Q&A sessions
- Self-directed project completion
- Certificate upon demonstration
Guided Cohort
One-time payment
- All Independent Study features
- Weekly live instruction sessions
- Direct instructor feedback
- Structured project deadlines
- Peer review participation
- Priority support access
- Portfolio review sessions
Mentored Program
One-time payment
- All Guided Cohort features
- Six individual mentoring sessions
- Personalized strategy development
- Custom portfolio architecture review
- Three months post-program support
- Advanced optimization techniques
- Direct communication channel
Where graduates are now
These aren't overnight transformations. Each person invested months of focused work to reach their current position. Results reflect individual effort and market conditions during their active periods.
From Manual Trading to Automated Systems
Astrid Kvalvik entered the program in June 2024 with five years of manual trading experience. She now operates three automated strategies managing a combined portfolio value exceeding CAD $300,000, with monthly rebalancing and defined exit parameters.
11 months to full automation
Career Transition Through Technical Skills
Zara Kildare joined with no programming background in March 2024. By December, she'd secured a junior quantitative analyst position at a Toronto investment firm, directly attributing the role to portfolio automation skills demonstrated during interviews.
9 months to new career pathReady to approach investment automation seriously?
Next cohort begins March 2026. Enrollment opens January 15, 2026, with limited capacity for guided and mentored programs. Independent study accepts registrations on a rolling basis.