2023H1 Classroom Training Course

Machine Learning for Time Series Forecasting

Quick learning to use Python and TensorFlow


Apply Online  PDF Form

A complete hands-on machine learning tutorial for Time Series Analysis Using Data Science, Artificial Intelligence and Neural Networks

This machine learning training course

consists of 4 full-day or 10 evening face-to-face training sessions. After completing the course, you will be able to use artificial intelligence to forecast sales data, stock prices, foreign currency exchange rates, etc.

We will focus on learning how to use machine learning in time series analysis as business managers, professionals like accountants, and investors.

this course brochure

中文   English

This training course helps you

  • learn how to work as a data scientist and machine learning practitioner in a business role

  • prepare you for the career path of the near future

  • learn to forecast sales data, stock prices, foreign currency exchange rates

Who this course is for?

Business managers and executives

who want to leverage data science and machine learning in sales forecasting operations

Professionals

in finance, accounting or other non-tech industries looking to master how AI can assist businesses

Investors

who explore new tech tools to help prediction

Technologists

interested in how to use machine learning


4 full-days or

10 evenings

classroom training

Face-to-face

interactive tutorial

30+

guided classroom exercises

Practical use

after class

Quick learning to use Python and Google TensorFlow

Every concept in this classroom training is introduced in Cantonese and written in English. The course avoids academic jargon or in-depth mathematical formulas. You will use Python programming code and a variety of programming libraries to learn concepts, knowledge, and exercises. You can keep the code for practical use after class.

Complete hands-on machine learning tutorial

In each class we provide exercises and tutorials to practice what you have learned. Hands-on exercises strengthen your understanding of course knowledge. All exercises are tailored for the training sessions. You can get programming code after class, or you can apply it to your work or investment analysis.

Course outlines

Take a short and quick look back at the research development in Time Series Analysis over the past few decades and see why artificial intelligence (AI) and machine learning (ML) play an important role in various fields of business and finance now and in the future.

We will learn how data scientists can manage and manipulate data using the Python programming language and related libraries. You could practice hands-on supervised machine learning, linear regression, artificial neural networks (ANN), convolutional neural networks (CNN), recurrent neural networks (RNN), building machine learning models and how to evaluate model performance. You will leverage the TensorFlow and Keras machine learning frameworks.

If you’re new to Python programming, don’t worry! We start with a crash course in Python. You will know and practice several Python suites: NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, Seaborn and more. You will also learn some time series analysis machine modelling technique that data scientists use.
We are going to study and learn machine learning and several supervised modelling techniques through examples and exercises. The learning focus of machine learning training and programming for time series analysis include univariate input, multivariate input, and univariate output. We'll also see how to establish baseline metrics to evaluate our prediction models.
Before training a machine model, it is necessary to prepare training and validation datasets. During our training sessions, we use APIs to obtain online financial data for our prediction exercises. On the downloaded dataset, we will learn and practice various methods of preparing the dataset: data cleaning and transformation, imputation of missing values and adding features such as futures settlement date, SP500 index, other stock indices, dividend dates etc.
Linear regression models are the most basic numerical forecasting method in data science. We'll take a detailed look at what it does, and use various Python libraries in case exercises to forecast sales.
In practicing ANN to predict forex prices, we will use TensorFlow and Keras to build a predictive model architecture, and discuss and practice how to optimize hyperparameters for machine learning training results.
Use an LSTM RNN to predict stock prices and explore tuning training parameters to study model performance with different stacked layers. We will also learn a MIMO (Multivariate Input Multivariate Output) model to predict the High, Low, Close Prices of a stock.
RL has been an exciting area of ML in recent years. It is used in DeepMind's AlphaGo, AlphaZero, AlphaFold and many interesting applications such as games and autonomous driving. We will discuss how RL can be used to build investment policies and automate operations for financial portfolio optimization.

Course prerequisites

Bring your own device

Bring your computer and be able to run Google Chrome browser with your Google login

Programming experience

Some prior coding or scripting experience required

Academic background

At least DSE / high school level math and computer skills

2023 Course schedules & fees

Day class : 9:30am – 5:00pm (HK$10,000)

Night class : 7:30pm – 9:30pm (HK$12,000)

Training venue : Wanchai / Sheung Wan / Jordon / Kwun Tong (select one venue for your classes at course registeration.)

Lauguage : Cantonese and English written materials (粵語授課並以英文作書面材料)

March

Day/Night Class
Course Code
Date
4 week days
2303MLT-D01 7-10 (Tue-Fri) Mar 2023
4 week days
2303MLT-D02
21-24 (Tue-Fri) Mar 2023
10 week day nights
2303MLT-E01
Every Tue & Thu, from 2 March to 4 April

April

Day/Night Class
Course Code
Date
4 week days
2304MLT-D01 18-21 (Tue-Fri) Apr 2023
4 week days
2304MLT-D02
25-28 (Tue-Fri) Apr 2023
10 week day nights
2304MLT-E01
Every Wed, Thu & Fri, from 12 April to 3 May

May

Day/Night Class
Course Code
Date
4 week days
2305MLT-D01 9-12 (Tue-Fri) May 2023
4 week days
2305MLT-D02
22-25 (Mon-Thu) May 2023
10 week day nights
2305MLT-E01
Every Tue & Thu, from 2 May to 1 June

June

Day/Night Class
Course Code
Date
4 week days
2306MLT-D01 6-9 (Tue-Fri) June 2023
4 week days
2306MLT-D02
13-16 (Tue-Fri) June 2023
10 week day nights
2306MLT-E01
Every Tue & Thu, starting from 6 June to 11 July

How to apply

Register

Online or download PDF form, fill it up and send it back to us.

On registration, select your preferable training venue and payment method.

Pay

For online pay, we'll send you the payment link.

For offline pay, we accept your direct bank-in payment.

Prepare

We'll send you a successful registration notification via email or WhatsApp.

Students will be given a Student Pack to get more detail for attending classes.

Attend

Before class commencement date, we'll send you reminder message.

Enjoy your study!

Course Detail

Notices to Students

We also provide on-site employee training service to tailor-made courses or English speaking classes for companies.