Mengidentifikasi tujuan pertanyaan

Bronwen sedang menyusun beberapa survei yang akan dikirimkan kepada pelanggan Wine Not?, layanan langganan wine. Satu survei dikirim ke sekelompok pengguna inti untuk mengumpulkan pernyataan positif tentang wine yang akan digunakan dalam materi pemasaran. Survei lainnya adalah survei kecil pada subset acak pengguna yang akan digunakan untuk mengurangi risiko keputusan tim Produk terkait peluncuran langganan hadiah baru. Survei terakhir adalah pop-up yang muncul setelah pelanggan menerima kiriman terbaru mereka untuk memantau kualitas setiap kotak baru.

Latihan ini adalah bagian dari kursus

Data Science untuk Bisnis

Latihan interaktif praktis

Ubah teori menjadi tindakan dengan salah satu latihan interaktif kami.

Mulai berolahraga

Latihan ini adalah bagian dari kursus

Data Science untuk Bisnis

SkillTag.level.beginnerSkillTag.label

4.8+

Mulai Kursus Gratis

We'll start the course by defining what data science is. We'll cover the data science workflow, and how data science is applied to real-world business problems. We'll finish the chapter by learning about ways to structure your data team to meet your organization's needs.

Exercise 1: What is Data Science?Exercise 2: Customer Segmentation Workflow Exercise 3: Building a customer service chatbot Exercise 4: Improving OKRs Exercise 5: Applications of Data Science Exercise 6: Assigning data science projects Exercise 7: Investment research Exercise 8: Building a data science team Exercise 9: Interpreting a team sprint Exercise 10: Editing a job posting Exercise 11: Matching skills to jobs Exercise 12: Classifying data tasks

Now that we understand the data science workflow, we'll dive deeper into the first step: data collection. We'll learn about the different data sources your company can draw from, and how to store that data once it's collected.

Exercise 1: Sumber data dan risikonya Exercise 2: Klasifikasi data untuk keamanan Exercise 3: Membuat event data web Exercise 4: Melindungi PII Exercise 5: Data yang diminta Exercise 6: Mengidentifikasi tujuan pertanyaan

Latihan Saat Ini

Exercise 7: Memvalidasi umpan balik focus group Exercise 8: Net Promoter Score Exercise 9: Mengumpulkan data tambahan Exercise 10: Mengelompokkan sumber data Exercise 11: Frekuensi asma Exercise 12: Penyimpanan dan pengambilan data Exercise 13: Platform cloud Exercise 14: Mengkueri basis data Exercise 15: Jenis basis data yang mana?

In this chapter, we'll discuss ways to explore and visualize data through dashboards. We'll discuss the elements of a dashboard and how to make a directed request for a dashboard. This chapter will also cover making ad hoc data requests and A/B tests, which are a powerful analytics tool that de-risk decision-making.

Exercise 1: Dashboards Exercise 2: Classifying dashboard elements Exercise 3: Improving a dashboard Exercise 4: Choosing the right dashboard Exercise 5: Ad hoc analysis Exercise 6: Filling out an ad hoc request Exercise 7: Classifying requests Exercise 8: A/B Testing Exercise 9: Creating an A/B testing workflow Exercise 10: Sample size Exercise 11: Intermediate results

In this final chapter, we'll discuss the buzziest topic in data science: machine learning! We'll cover supervised and unsupervised machine learning, and clustering. Then, we'll move on to special topics in machine learning, including time series prediction, natural language processing, deep learning, and explainable AI!

Exercise 1: Supervised machine learning Exercise 2: When to use Supervised Learning Exercise 3: Features and labels Exercise 4: Model evaluation Exercise 5: Clustering Exercise 6: Supervised vs. unsupervised Exercise 7: Cluster size selection Exercise 8: Special topics in Machine Learning Exercise 9: Classifying machine learning tasks Exercise 10: Sentiment Analysis Exercise 11: Deep Learning and Explainable AI Exercise 12: Finding the correct solution Exercise 13: Should I use Deep Learning?