Advanced Time Series Analysis with Python
Take your time series forecasting skills to the next level by learning how to apply advanced statistical methods, machine learning, and deep learning to real-world forecasting challenges using Python.
Start for free
What you get:
- 6 hours of content
- 43 Interactive exercises
- 13 Downloadable resources
- World-class instructor
- Closed captions
- Q&A support
- Future course updates
- Course exam
- Certificate of achievement
Advanced Time Series Analysis with Python
Start for free
What you get:
- 6 hours of content
- 43 Interactive exercises
- 13 Downloadable resources
- World-class instructor
- Closed captions
- Q&A support
- Future course updates
- Course exam
- Certificate of achievement
Start for free
What you get:
- 6 hours of content
- 43 Interactive exercises
- 13 Downloadable resources
- World-class instructor
- Closed captions
- Q&A support
- Future course updates
- Course exam
- Certificate of achievement
What you learn
- Dynamic Regression
- Generalised Additive Models
- XGBoost
- Recurrent Neural Networks
- Long Short Term Memory
- Gated Recurrent Unit
- Vector Autoregression
- Prophet
- Vector Error Corrected Model
Top Choice of Leading Companies Worldwide
Industry leaders and professionals globally rely on this top-rated course to enhance their skills.
Course Description
This course builds on your foundational time series knowledge to help you explore more advanced concepts and models in the field.
You’ll gain hands-on experience with techniques such as:
- Generalised Additive Models and Splines
- Dynamic Harmonic Regression
- Vector Error Correction Models
- Recurrent Neural Networks
- Gradient Boosted Trees
By the end of the course, you’ll have a strong understanding of complex forecasting models and the practical insight to know when and how to apply them in real-world scenarios.
Learn for Free
1.1 Welcome!
4 min
1.2 Pre-Requisites
2 min
2.1 Installing Git and Github
1 min
2.3 Installing Course Notebooks
5 min
Curriculum
- 2. Coding Environment3 Lessons 7 MinInstalling Git and Github Read now1 minInstalling Anaconda and Jupyter Notebook Read now1 minInstalling Course Notebooks5 min
- 3. Dynamic Models5 Lessons 55 MinSection Intro Read now2 minDynamic Regression Read now6 minDynamic Regression Python Tutorial25 minDynamic Harmonic Regression Read now6 minDynamic Harmonic Regression Python Tutorial16 min
- 4. Advanced Statistical Models9 Lessons 106 MinSection Intro Read now1 minNon-Linear Regression and Generalised Additive Models Read now9 minNon-Linear Regression Python Tutorial19 minProphet Read now2 minProphet Python Tutorial20 minVector Autoregression Read now6 minVector Autoregression Python Tutorial22 minVector Error Correction Model Read now9 minVector Error Correction Model Python Tutorial18 min
- 5. Machine Learning Models7 Lessons 109 MinSection Intro Read now2 minK-Nearest Neighbour & Dynamic Time Warping Read now11 minK-Nearest Neighbour Python Tutorial21 minTree Based Models Read now22 minTree Based Models Python Tutorial21 minNeural Network Read now12 minNeural Network Python Tutorial20 min
- 6. Deep Learning7 Lessons 85 MinSection Intro Read now1 minRecurrent Neural Network Read now10 minRecurrent Neural Network Python Tutorial39 minLong-Short Term Memory Read now7 minLSTM Python Tutorial13 minGated Recurrent Unit Read now4 minGRU Python Tutorial11 min
- 7. Further Notes4 Lessons 25 MinSection Intro Read now1 minApproaching Forecasting Problems13 minStatistical vs Deep Learning Models Read now6 minTaxonomy of Forecasting Models Read now5 min
Topics
Course Requirements
- Basic understanding of Python
- Fundamentals of time series forecasting
- Basic understanding of machine learning
- Familiarity with the PyData stack: Numpy, Pandas, Plotly, Sci-Kit Learn
Who Should Take This Course?
Level of difficulty: Advanced
- People familiar with the fundamentals of time series forecasting and machine learning
Exams and Certification
A 365 Financial Analyst Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.
Meet Your Instructor
Egor Howell
1 Courses
3 Reviews
31 Students
Data Scientist & Machine Learning Engineer specialising in applied machine learning, time series forecasting and optimisation / operations research problems.
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