Forecasting Mobile Network (Internet) Traffic with Recurrent Neural Network

Learn how to predict the mobile traffic load with high accuracy using Python.

  • Schedule

    20 – 22 September 2022

    18.30 – 21.30 (WIB)

  • Online-Interactive Learning

    Via Zoom

  • Investment

    Rp. 1.500.000

Course Summary

Since the pandemic, people have shifted their daily habits and increased their time spent on the internet. The new patterns also raise a new demand: fast and reliable internet networks. As the number of internet users increases, the bandwidth for the services also needs to be increased. To continue providing the best service to customers, internet service providers should take advantage of data science.

By performing time series analysis using the Recurrent Neural Network (RNN) model, internet service providers can estimate how much bandwidth they need and manage network resources more efficiently. Estimations can be achieved by analyzing the characteristics of users and their area coverage for a particular time.

This 3-day online workshop is a beginner-friendly introduction to Forecasting Mobile Network (Internet) Traffic with RNN. By performing time series analysis on your historical business data and comparing it with current trends, you will be able to make a more informed decision. 

Throughout the online course, we will provide participants with a rich interactive experience. One Instructor and two Teaching Assistants will help participants to troubleshoot or help with any difficulties encountered by participants.

NOTE: This workshop will be delivered in Bahasa Indonesia.


Upon completion of this workshop, you will be able to:

  • Work with Python and pandas for data cleansing and manipulation processes.
  • Understand deep learning architecture.
  • Work with Tensorflow for training data.
  • Understand model reusability.


  • Working with Conda Environment
  • Introduction to Python for data science
  • Data manipulation and processing with Python Pandas
  • Layer and neurons
  • Activation and cost function
  • Feedforward
  • Backpropagation
  • Sequence Models
  • Vanilla RNN
  • Long Short-Term Memory (LSTM)
  • Bidirectional and Deep RNN
  • Time series Forecasting
  • Visualize the time series
  • Training with validation: define the architecture, compile the model, model fitting and evaluation
  • Testing on unseen data


This testimonial video is taken after our previous Online Data Science Series: Time Series Analysis for Business Forecasting.


Our learning format is online-interactive, you will feel the interactive experience as if you were present in a physical classroom. You can access the class using your Zoom account on pre-defined dates.


    Zoom recording, course Books (PDF & HTML files), the dataset for practice, reference notes, and working files are accessible through our Learning Management System account.


    Show current and prospective employers of your mastery in computer vision with a signed certificate of completion.


    Be a part of our data-passionate community with 5000+ members and 1000+ alumni.


Workshops in this series are tailored to casual programmers and non-programmers that are taking their first steps into data science. It assumes no prior knowledge or academic background, and attendees will be introduced to the beautiful art of writing R / Python code to produce data visualization and build machine learning models. The workshop has a gentle learning slope that is designed with non-technical professionals and academics in mind.

Yes, you can still attend the workshop as it is a beginner-friendly workshop.

Our system will send you an email containing a link and details to join a Google Classroom.

Online learning will be conducted via Zoom.us, Link to join the Zoom Class will be announced via Google Classroom.

Learning materials can be obtain via Google Classroom

Yes, you will receive a certificate of completion.


Wulan Ayu

A Data Science Instructor at Algoritma Data Science School who is proficient in Machine Learning implementation. She is a passionate Instructor with expertise in both R and Python programming languages. Wulan has been involved in numerous mentoring, data science projects, and consultative data science training for Bank Central Asia and Telkom.