Overview

This three-day course is aimed at those who are familiar with data analysis and are interested in learning about how to analyse, model, and generally yield value from time series assets.

This course will be of interest if you are interested in developing your own skills to move from analytics to Data Science, or if you are working with Data Scientists and want to learn more about what is possible when working with time data.

You will be introduced to key concepts and tools for use in time series analysis and forecasting including time series characteristics, time series components, time based statistics, model development, exploratory analysis and visualisation, as well as techniques and strategies for model deployment.

Throughout the course you will engage in activities and discussions with one of our Data Science technical specialists. Theoretical modules are complimented with comprehensive practical labs.

Target Audience

Members of the audience are required to have a some technical expertise such as table structure, working with tabular data in Python, and simple data analysis.

They may be Mid/Senior Leadership seeking a greater understanding of how to implement Data Science within their organization.

They may come from other technical backgrounds such as Data Analysts, Software Developers, and Data Engineers who either work with Data Scientists or are using this course in their journey towards training as a Data Scientist.

In the latter case, audience members may ask for recommendations for their next steps in training towards becoming Data Scientists. We recommend the following refreshed courses which are due to launch in 2023 and 2024 in this suggested sequence:

  • Maths and Statistics for Data Science with Python
  • Practical Big Data Analytics (with Python and Spark)
  • Generative AI Essentials
  • Fundamentals of Deep Learning with Python (followed by selected Python & NVIDIA training)

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Prerequisites

We recommend that delegates are familiar with fundamental data science concepts, such as those found on our QA Introduction to Data Science for Data Professionals, as well as programming techniques found in QA Python for Data Handling. You should also have an interest in developing Data Science within your organisation or in becoming a Data Scientist.

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Outline

1. Introduction to Time Series Forecasting

  • Interpreting time series visualisations and understanding the business need for forecasts
  • Identify decomposition components: trend, seasonality, noise
  • Identify methods for handling shocks
  • Calculate a moving average
  • Identify how regression methods can be applied in simple forecasts

2. Introduction to Forecasting with ARIMA

  • Use of Python to forecast with Arima methods
  • Model development and testing process
  • Tuning and assessing the forecasting model

3. Time Series Modelling with Prophet

  • Exploration of Facebook Prophet
  • Build and evaluate a model using prophet

4. Time Series Modelling with Deep Learning

  • Understand deep learning approaches for time series modelling
  • Build a deep learning time series model
  • Evaluate a deep learning time series model

5. Time Series Modelling Activity

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Why choose QA

Dates & Locations

Need to know

Frequently asked questions

How can I create an account on myQA.com?

There are a number of ways to create an account. If you are a self-funder, simply select the "Create account" option on the login page.

If you have been booked onto a course by your company, you will receive a confirmation email. From this email, select "Sign into myQA" and you will be taken to the "Create account" page. Complete all of the details and select "Create account".

If you have the booking number you can also go here and select the "I have a booking number" option. Enter the booking reference and your surname. If the details match, you will be taken to the "Create account" page from where you can enter your details and confirm your account.

Find more answers to frequently asked questions in our FAQs: Bookings & Cancellations page.

How do QA’s virtual classroom courses work?

Our virtual classroom courses allow you to access award-winning classroom training, without leaving your home or office. Our learning professionals are specially trained on how to interact with remote attendees and our remote labs ensure all participants can take part in hands-on exercises wherever they are.

We use the WebEx video conferencing platform by Cisco. Before you book, check that you meet the WebEx system requirements and run a test meeting (more details in the link below) to ensure the software is compatible with your firewall settings. If it doesn’t work, try adjusting your settings or contact your IT department about permitting the website.

How do QA’s online courses work?

QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course. When you book a QA online learning course you will receive immediate access to it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.

All courses are built around case studies and presented in an engaging format, which includes storytelling elements, video, audio and humour. Every case study is supported by sample documents and a collection of Knowledge Nuggets that provide more in-depth detail on the wider processes.

When will I receive my joining instructions?

Joining instructions for QA courses are sent two weeks prior to the course start date, or immediately if the booking is confirmed within this timeframe. For course bookings made via QA but delivered by a third-party supplier, joining instructions are sent to attendees prior to the training course, but timescales vary depending on each supplier’s terms. Read more FAQs.

When will I receive my certificate?

Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.

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