Studium Generale STA111 Statistika dan Analisis Data

Kuliah Umum atau disebut juga studium general merupakan suatu kegiatan yang dilaksanakan oleh sebelum dimulainya kuliah efektif pada paruh kedua Semester Genap 2021/2022. Kuliah umum ini bertujuan untuk memotivasi mahasiswa dalam menjalani kuliah efektif pada minggu- minggu berikutnya dengan memberikan materi-materi yang membuka wawasan dan menambah keilmuan baru tentang penerapan ilmu statistika dan sains data modern di berbagai bidang.

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1. Berkarya Di Bidang Data Di Digital Company Photo by Tomas Sobek on Unsplash.This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator.
2. Outline This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator. Data Professionals Digital Company Data Driven Roles in Data Data Tasks How to Start Portfolio Learning Sources Use Cases CRISP-DM
3. Data Professionals Photo by Stephen Dawson on Unsplash.This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator.
4. Largest Market Cap Company Photo by Wikipedia. This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator. 2011 2021 Source: Wikipedia
5. Accommodation company owns no hotel Digital Company Taxi company owns no car Retailer carries no inventory Media company owns no content • Innovate through digital ecosystem • New way of working • Growth exponentially • Data driven Digital Start-ups: This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator.
6. Telkom Digital Photo by Telkom Digital This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator. leap.digitalbisa.id
7. Data Driven Photo by Brend Dykes on Forbes.This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator. Data information Insight Action Source: Dykes B , Forbes Aggreagete, summary, statistics Analyzing information and drawing conclusions Problem solving or make changes Raw and unprocessed facts
8. Data Science Photo by Shyue Pinf Ong on UC San Diego and Gartner. This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator. Data Science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data - Shyue Ping Ong, UC San Diego Source: UC San Diego Source: Gartner
9. Data Science Roles Icons made by Euclayp, Becris, Mynamepong, and Catkuro from www.flaticon.com. This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator. • Knowledge of database • Ability to query data (SQL, NoSQL) • Ability to describe data (Trends, changes, etc) • Ability to use visualisation tools (Tableau, PBI) • Fluent at spreadsheet (Excel, sheet) • Ability to present data (Slides, Dashboards) • Business Acumen • Data Modeling (Statistical/Machine Learning) • Conduct Research • Experiment (A/B testing) • Extract insights, Tell Story • Programming (Python, R, ..) • Knowledge of database architecture • Knowledge of cloud platforms • Data pipeline (ETL) • Programming (Python, Scala, Java..) • State-of-the art machine learning models • Deep Learning • Computer Vision, NLP • Model deployment ++Adv. Statistics Data Scientist ++Data Engineering Data Engineer ++Software Engineering Machine Learning Engineer ++Business Business Intelligence ++Product Product Analyst Data Analyst
10. Data Tasks Photo by Stephen Dawson on Unsplash.This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator.
11. Use Cases Regression Clustering Classification Icons made by Flat Icons from www.flaticon.com. This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator.
12. Use Cases Statistics Visualization Icons made by Flat Icons from www.flaticon.com. This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator.
13. CRISP-DM This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator. 1. Business understanding – What does the business need? 2. Data understanding – What data do we have / need? Is it clean? 3. Data preparation – How do we organize the data for modeling? 4. Modeling/Analysis – What modeling/analysis techniques should we apply? 5. Evaluation – Which model best meets the business objectives? 6. Deployment – How do stakeholders access the results? The CRoss Industry Standard Process for Data Mining (CRISP-DM) consist of:
14. How to Start Photo by Stephen Dawson on Unsplash.This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator.
15. Portfolio Level Up with Learnings Compete in competitions Publishing your Masterpieces Get an Internship or a Job Join Communities This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator. • Data Course • Online Training • Bootcamp • Certification Evidence: Grade, Certificate • Kaggle/Hackerrank • Data Competition • National Competition • Hackathon Evidence: Awards, Codes • GitHub • Medium • Research Papers Evidence: Codes, Writings, Blogs, etc. • Internship • Project • Contract Based Evidence: Internship/ Employment Letter • Community Event • Volunteering • Lecturing/Mentoring Evidence: Certificates, Token of Appreciation
16. Learning Sources This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator. Belajar (Learn) Tantangan (Challenge)
17. That’s All My Contacts https://www.linkedin.com/in/iqbal-hanif-a7599662/ My Articles/Writings My Portfolios https://www.researchgate.net/profile/Iqbal_Hanif https://medium.com/@iqbalhannif https://github.com/iqbalhanif https://speakerdeck.com/iqbalhanif This document created by Iqbal Hanif. Not for sale & distribution without permission from its creator.