Master time series forecasting from the ground up through one cohesive, real-world project: predicting global semiconductor chip sales and NVIDIA stock prices. This hands-on course takes you through the complete forecasting workflow—acquiring data from APIs and public sources, wrangling and engineering features, running EDA, and building models that actually ship. You'll implement the full spectrum of techniques: classical statistical models (ARIMA, SARIMA, SARIMAX, Prophet), tree-based machine learning (XGBoost, LightGBM with Optuna tuning), and deep learning architectures (LSTM, GRU, CNN-LSTM, Temporal Fusion Transformers). Go further with multivariate analysis using Granger causality, VAR, and VECM to uncover how chip sales and stock prices influence each other, then combine everything into ensemble and hybrid pipelines. Finally, deploy your best model as a live FastAPI endpoint and an interactive Streamlit dashboard, complete with automated retraining and cloud deployment. Across 4 modules and 48 concise videos, you'll build a portfolio-ready, end-to-end forecasting system that demonstrates production-grade skills employers value.

Time Series Forecasting with Python: Models to Production

Time Series Forecasting with Python: Models to Production

Instructor: Board Infinity
Included with Learn more
Ask Coursera
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Build and evaluate statistical models: exponential smoothing, Holt-Winters, ARIMA, SARIMA, SARIMAX, and Prophet.
Implement deep learning architectures: LSTM, GRU, CNN-LSTM hybrids, and Temporal Fusion Transformers.
Frame forecasting as supervised learning and train tree-based models with leak-free time series cross-validation.
Skills you'll gain
- Feature Engineering
- Model Evaluation
- Applied Machine Learning
- Statistical Analysis
- Recurrent Neural Networks (RNNs)
- Time Series Analysis and Forecasting
- Data Preprocessing
- MLOps (Machine Learning Operations)
- Correlation Analysis
- Data Wrangling
- Statistical Modeling
- Supervised Learning
- Forecasting
- Deep Learning
- Model Training
- Statistical Methods
- Machine Learning
- Predictive Modeling
Tools you'll learn
Details to know

Shareable certificate
Add to your LinkedIn profile
Recently updated!
June 2026
Assessments
16 assignments
Taught in English
See how employees at top companies are mastering in-demand skills

There are 4 modules in this course
Instructor

Offered by
Explore more from Data Analysis
Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."

Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."

Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."

Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Advance your career with an online degree
Earn a degree from world-class universities - 100% online






