Let's start with the importance of data storytelling and the elements you need to tell stories with data. You'll learn best practices to influence how decisions are made before learning how to translate technical results into stories for non-technical stakeholders.


Fundamentals of storytelling

The story begins

Building a story

Translating technical results

A non-tech story

Be aware

Impacting the decision-making process

Is it a true story?

Structured to impact

A story to compare

Storytelling with Data

Deepen your storytelling knowledge. Learn how to avoid common mistakes when telling stories with data by tailoring your presentations to your audience. Then learn best practices for including visualizations and choosing between oral or written formats to make sure your presentations pack a punch!


Selecting the right data

The truth about salaries

Earning interests

Showing relevant statistics

Salary variation

On a payroll

It's not significant

Visualizations for different audiences

Salary development

Salary on demand

Choosing the appropriate format

A communication problem

Should we meet?

When in doubt

Preparing to Communicate the Data

Now that you understand how to prepare for communicating findings, it’s time to learn how to structure your reports. You'll also learn the importance of reproducibility (work smarter, not harder) and how to get to the point when describing your findings. You’ll then get to apply all you’ve learned to a real-world use case as you create a compelling report on credit risk.


Jenis-jenis laporan

Laporan Data Science

Sesuatu untuk Dilaporkan

Opsi

Laporan final

Laporan ringkasan

Sebagai ringkasan

Reproduksibilitas dan referensi

Replikasi saya

Praktik buruk

Praktik terbaik

Hasil yang sama

Tulis laporan yang tepat dan jelas

Masih bisa diperbaiki

Jelas dipahami

Gelas setengah kosong

Dapat diperbaiki

Mudah dipahami

Kata-kata yang kuat

Studi kasus: laporan tentang risiko kredit

Credit me

Laporan Ringkasan

Laporan kredit saya

Structuring Written Reports

You'll finish by learning simple techniques to structure a presentation, communicate insights, and inspire your audience to take action. Lastly, you'll learn how to improve your communication style and prepare to handle questions from your audience.


Planning an oral presentation

Is this the plan?

An effective plan!

Building presentation slides

A color building

Too much text

The right building

Delivering the presentation

Put it into practice

Best practice

Avoiding common errors

The true mistake

Do's and don'ts

Congratulations!

Building Compelling Oral Presentations

Anda telah menganalisis data, menjalankan model, dan membuat prediksi. Sekarang, saatnya menghadirkan data Anda! Menyajikan temuan kepada pemangku kepentingan agar mereka dapat mengambil keputusan berbasis data adalah keterampilan penting bagi semua data scientist. Dalam kursus ini, Anda akan belajar menggunakan storytelling untuk terhubung dengan audiens dan membantu mereka memahami isi presentasi—agar mereka dapat mengambil keputusan yang tepat. Melalui latihan praktis, Anda akan mempelajari kelebihan dan kekurangan format lisan dan tertulis. Anda juga akan meningkatkan kemampuan menerjemahkan hasil teknis menjadi cerita yang menarik, menggunakan data yang tepat, visualisasi, dan teknik presentasi langsung. Mulailah belajar dan tingkatkan kemampuan data storytelling Anda hari ini.

Video dilengkapi transkrip langsung yang dapat Anda tampilkan dengan mengklik "Show transcript" di kiri bawah video.									
Glosarium kursus dapat ditemukan di sisi kanan pada bagian sumber daya.
									
Untuk memperoleh kredit CPE, Anda perlu menyelesaikan kursus dan mencapai skor 70% pada asesmen yang memenuhi syarat. Anda dapat menuju ke asesmen dengan mengklik ajakan kredit CPE di sisi kanan.									

Understanding Data Science

Understanding Data Visualization

Tidak ada yang suka melihat spreadsheet! Hidupkan data Anda. Tingkatkan presentasi dan ubah data jadi wawasan.

Konsep Komunikasi Data

Analis Data Asisten dalam SQL

Associate Data Scientist di R

Associate Data Scientist  dalam Python

The project had the aim to create a model that can predict the average house price in the state of Colorado.

Mean house price increases as the number of rooms increases from range 1 to 3. It should be pointed out that prices decrease for more than 5 rooms.

The results should be interpreted carefully through the lens of a real-estate bubble situation.

The project pursued the creation of a model that can predict the average house price in the state of Colorado.

Mean house price increases as the number of rooms increases from range 1 to 3. For more than 5 rooms, the price decreases.

The results should be interpreted carefully considering the real-estate bubble situation.

Gelas setengah kosong

Konsep Komunikasi Data

Latihan interaktif praktis