fbpx

Data Science Series:
Building a Sales Forecasting App for Beginners

3

Days

Course details :

This 3-day workshop is a beginner-friendly introduction to time series and forecasting.

If you ever wondered how forecasting apps are built, dive in with us in this hands-on machine learning workshop led by Algoritma’s acclaimed team of instructors. The workshop combines time series theories, hands-on coding and programming sessions to help students understand — and implement — some of the most widely used forecasting techniques.

By building a forecasting model, students will be able to use time series data to improve your business decision making skills. You will also be guided in building your own app using Shiny Apps in R.

* The 3-day workshop is taught in Bahasa Indonesia

“The most reliable way to forecast the future is to try to understand the present. ”
~ John Naisbitt, American Author

Please bring along:

  • 1x Laptop
  • Purchased ticket (from organizer’s website)

Partners:

Schedule

  • Time Series Data and Forecasting

    The basics and different methods of time series and forecasting

    Day 1

  • Frequency Conversion

    Handling incomplete data with frequency conversion & different techniques of frequency conversion

    Day 1

  • ARIMA for Time-Series Analysis

    Practical analysis using ARIMA

    Day 1

  • Time Series Component

    Seasonal, trend, and random pattern

    Day 2

  • Exponential Smoothing

    Intuitive explanation of exponential smoothing techniques

    Day 2

  • Building Shiny Dashboard

    Understanding shiny component & step-by-step hands-on coding creating your own apps

    Day 3

  • Deploying Shiny Apps

    Sharing your shiny apps with others

    Day 3

Event Ended
Explore other data science workshops

Trainer

  • Iffa

  • Arfika

 

Iffadathul Faddilla

Arfika Nurhudatiana

Detailed Syllabus

Syllabus: Building a Sales Forecasting App for Beginners

Time Series Data

  • Basics of time series
  • ARIMA for time series analysis
  • Where to find time series data
  • Practical analysis using ARIMA

Forecasting

  • Basics of forecasting
  • Different methods for forecasting

Frequency conversion

  • Introduction to frequency conversion
  • Handling incomplete data with frequency conversion
  • Different techniques of frequency conversion
  • Practice using a simple dataset

Time Series and Component

  • Introduction to time series data and forecasting
  • Time series data component
  • Additive and multiplicative
  • Data transformation

Exponential Smoothing Technique

  • Concept Exponential Smoothing
  • Single Exponential Smoothing
  • Holt’s Method
  • Holt-Winter’s Method

Building Shiny Dashboard

  • Understanding shiny component and how it works
  • Basic component required in shiny apps
  • Step-by-step hands-on coding creating your own apps
  • Code example of forecasting app for time series data

Deploy Shiny Apps

  • Customizing your shiny apps
  • How to share your apps with others
  • Publish apps to shinyapps.io

This workshop will cost 3 workshop credits for subscribers. Non-subscribers are welcomed to participate at a cost of IDR 3,000,000.

Workshop Receivables:

  • Workshop Lecturer’s Notes

    Including 2x Course Books (PDF), HTML files, course transcripts (if any).

  • Highly-accelerated Learning

    Learn under the assistance of mentorship of our lead instructor and a band of qualified teaching assistants throughout the 3 day course.

  • Certification of Completion

    Show current and prospective employers that you’ve completed the course with a signed certificate of completion.

  • Quality Learning Environment

    We pay meticulous attention to the logistical details of our workshops: quality audio and visual setups, comfortable sitting arrangements, small group size. Dinners are included for evening workshops.

  • Supplement Materials

    Receive supplement datasets to practice on, reference notes, working files (R Notebook or Jupyter Notebook), and other materials that will help you master the topics.

Data Science Series

Workshops in our Data Science Series are tailored to casual learners, working professionals and non-programmers that are taking their first steps into data science and machine learning.

Students are not assumed to have a working knowledge of R or prior proficiency in statistics / mathematics / algebra. At such the workshop follows a gentle learning curve and emphasize on hands-on, one-to-one tutoring from our team of instructors and teaching assistants.

Consider taking our Data Science Intermediate workshops instead for more advanced-level materials in statistical programming and machine learning.

Past Workshops in this Series:

Students work through tons of real-life examples using sample datasets donated by our team of mentors and corporate partners. We believe in a learn-by-building approach, and we employ instructors who are uncompromisingly passionate about your growth and education.