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Data Science for Marketing Insights
Rating: 4.5 out of 5(14 ratings)
154 students

Data Science for Marketing Insights

How to use Data Science procedures and tools to improve your marketing plans
Created byMuhammad Ammar Jamshed
Last updated 7/2022
English
English [Auto],

What you'll learn

  • How to apply Data Science methodologies at their workplace
  • It can be learnt easily by spending 1 hour per week
  • It contains case studies
  • A survey will be provided to what the course buyers gained and did not gain from the course

Course content

5 sections • 13 lectures • 53m total length

  • Introduction2:35

    This course will broaden your understanding of how data science is applied in marketing settings.

  • Data Science Intro
  • key points covered3:46

    Explore how data science applies to marketing by transforming structured, unstructured, and semi-structured data into insights, and distinguish data science from business intelligence and its machine learning foundations.

Requirements

  • No programming or stats required for entry

Description

In this course you will learn:

1. Data science and its process.

2. Integrating data science into marketing plans.

3. Types of data and how are they collected in marketing.

4. What tools are used by data scientists?

5. Marketing- intro, traditional and digital marketing.

6. Traditional marketing and digital marketing in Data Science.

7. Types of data needed by marketing professionals.

8. How data science is used in the marketing spectrum.

9. Business Intelligence Uses in marketing (What is it? How it is helpful?).

10. Business Intelligence vs Data Science.

11. Business Intelligence Tools.

We will further have labs on how to use PowerBI and Google Data Studio for manipulating and visualization of data and I will put all relevant links for you to download the tools directly.

I do know how tough it is to get a hang of new software and tools whenever starting new projects, but it all comes down to practice and commitment, I will help you find the direction in this course on how to better improve your work process in data analysis.

The rest will all be a result of your own efforts in trying to better yourself both as a learner and a professional.

Who this course is for:

  • Beginners in Data Science and business professionals

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