Time Series Forecasting with ML
From ARIMA to deep learning forecasters
About this program
Six months on modern forecasting. Classical methods (ARIMA, ETS, Prophet) before moving into gradient boosting and deep learning forecasters (N-BEATS, TFT, foundation models for time series). Real case studies from Canadian energy and retail.
Student ratings
Highly rated — 430 verified Canadian graduates rated this program 4.6/5. Reviews emphasize the applied capstone, instructor responsiveness, and career outcomes.
- 5★277
- 4★140
- 3★9
- 2★2
- 1★2
Who this program is for
- →Working professionals moving into data science roles
- →Analysts, developers, and product people leveling up on applied AI
- →Canadian residents seeking a verifiable diploma credential
Topics you'll cover
6 modules across 6 months — 24 lessons in total.
Full syllabus
Module 1 · Month 1 — Foundations▾
- L1Time-series basics
- L2Stationarity, decomposition
- L3Naive baselines
- L4Evaluation metrics
Module 2 · Month 2 — Classical Methods▾
- L1ARIMA family
- L2ETS
- L3Prophet
- L4Lab: retail forecasting
Module 3 · Month 3 — ML Forecasting▾
- L1Feature engineering
- L2XGBoost and LightGBM
- L3Cross-validation strategies
- L4Lab: energy demand
Module 4 · Month 4 — Deep Learning▾
- L1N-BEATS
- L2TFT
- L3DeepAR
- L4Foundation models (Chronos, TimesFM)
Module 5 · Month 5 — Hierarchies and Probabilistic▾
- L1Hierarchical reconciliation
- L2Quantile forecasts
- L3Conformal prediction
- L4Cost-aware forecasting
Module 6 · Month 6 — Capstone▾
- L1Real forecasting problem
- L2Compare methods
- L3Deploy and monitor
- L4Final report
What you'll be able to do
- ●Build production forecasters
- ●Choose the right method per problem
- ●Handle hierarchies and reconciliation
- ●Evaluate forecasts rigorously
- ●Communicate uncertainty
Career paths after graduation
Frequently asked questions
How much does the Time Series Forecasting with ML cost?▾
Tuition is $150 CAD, paid once. You can pay in full at checkout or choose an interest-free monthly plan. A 30-day refund window applies from your enrollment date.
How long is the Time Series Forecasting with ML program?▾
Self-paced. Most students complete it in 6 months at roughly 7 hours per week, but you can go faster or slower — you keep lifetime access.
What are the prerequisites?▾
Python; Basic statistics
Is the diploma recognized in Canada?▾
Yes. Graduates receive the Altaris AI Academy Diploma in Data Science — a verifiable credential with a unique certificate number you can publish on LinkedIn and that any employer can verify at altarisai.org/verify.
What is the refund policy?▾
Full refund within 30 days of enrollment, no questions asked. After day 30, prorated refunds are available per our Refund Policy.
Who teaches the program?▾
Working Canadian AI practitioners — not academics. Every module is built and reviewed by a lead instructor working in the field today.
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