The Analytics Translator – Data Science Career Development

The Analytics Translator – Data Science Career Development, available at $54.99, has an average rating of 4, with 56 lectures, based on 67 reviews, and has 432 subscribers.

You will learn about A better understanding of the role analytics translator and the link between Business, Analytics, and IT The content should illuminate the difference to data science and the challenges within the job role of an analytics translator. Support your personalised curriculum of the learning journey by a better understanding the connected terminology between multiple subjects. Part II: Generative AI overview and applied uses cases This course is ideal for individuals who are Every person who is interested in the role of an analytics translator. or Students during their studies hearing the 'analytics translator' role and want to know more or Persons moving into this job role or Persons in organizations launching business analytics teams and digital transformation or Persons interested how to embed generative AI in the work flow It is particularly useful for Every person who is interested in the role of an analytics translator. or Students during their studies hearing the 'analytics translator' role and want to know more or Persons moving into this job role or Persons in organizations launching business analytics teams and digital transformation or Persons interested how to embed generative AI in the work flow.

Enroll now: The Analytics Translator – Data Science Career Development

Summary

Title: The Analytics Translator – Data Science Career Development

Price: $54.99

Average Rating: 4

Number of Lectures: 56

Number of Published Lectures: 56

Number of Curriculum Items: 56

Number of Published Curriculum Objects: 56

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

A better understanding of the role analytics translator and the link between Business, Analytics, and IT
The content should illuminate the difference to data science and the challenges within the job role of an analytics translator.
Support your personalised curriculum of the learning journey by a better understanding the connected terminology between multiple subjects.
Part II: Generative AI overview and applied uses cases

Who Should Attend

Every person who is interested in the role of an analytics translator.
Students during their studies hearing the 'analytics translator' role and want to know more
Persons moving into this job role
Persons in organizations launching business analytics teams and digital transformation
Persons interested how to embed generative AI in the work flow

Target Audiences

Every person who is interested in the role of an analytics translator.
Students during their studies hearing the 'analytics translator' role and want to know more
Persons moving into this job role
Persons in organizations launching business analytics teams and digital transformation
Persons interested how to embed generative AI in the work flow

The role of analytics translator is not well defined, yet, an exciting, challenging, and emerging role for a future job profile.

Part I Gives an overview of 15 key capabilities that fall into the analytics, business, and IT know-how class to master the role of an analytics translator.

Part II (new update Oct 2023) delves deep into what the future holds for our workplaces, shining a light on the latest trends of generative AI and its use cases for the analytics translator.

Each learning path is different, and multiple topics and skills contribute to this job role. The content should illuminate the difference between data science and the vast learning possibilities within the job role of an analytics translator.

Thus, the goal is to drive your personalized curriculum of the learning journey by a better understanding of the connected terminology between other subjects.

The mission of the lecture: judge better on your analytics translator learning journey.

Analytics translators have the vital goal of integrating analytics capabilities in a company.

They identify value cases for the business that analytics can help solve.
Lead or support data science and IT teams in developing data-driven solutions to these problems.
They ensure the usage within business operations.
They have to be front runners in embedding new technologies like generative AI 🙂

The top domains for an analytics translator are fluent speaking and understanding business know-how, IT constraints, and analytics understanding.

The lecture derives from practical insights in strategically embedding this role in global digital transformation initiatives.

Course Curriculum

Chapter 1: Part I: Introduction

Lecture 1: 1.1 Lecture Goal

Lecture 2: 1.2 Procedure

Lecture 3: Possible Practices

Chapter 2: Part I: Skill Domains

Lecture 1: 2.1 Domains Overview

Chapter 3: Part I: Management

Lecture 1: 3.1 Management Executive Summary

Lecture 2: 3.2 Management Case Example

Lecture 3: Possible practice: write your own narrative

Chapter 4: Part I: Problem Solving

Lecture 1: Problem Solving Executive Summary

Lecture 2: Problem Solving Case Example

Lecture 3: Possible practice: your knowledge breakdown

Chapter 5: Part I: Sales Framework

Lecture 1: Sales Framework Executive Summary

Lecture 2: Sales Framework Case Example

Lecture 3: Possible practice: do an interview

Chapter 6: Part I: Product Management

Lecture 1: Product Management Executive Summary

Lecture 2: Product Management Case Interview

Lecture 3: Possible practice: interview with prototype

Chapter 7: Part I: Data

Lecture 1: Data Executive Summary

Lecture 2: Data Case Example

Lecture 3: Possible practice: enrich topic list

Chapter 8: Part I: Software Design

Lecture 1: Software Design Executive Summary

Lecture 2: Software Design Case Example

Lecture 3: Possible practice: automated wiki search

Chapter 9: Part I: Proof-of-Value

Lecture 1: Proof-of-Value Executive Summary

Lecture 2: Proof-of-Value Case Example

Chapter 10: Part I: Project Management

Lecture 1: Project Management Executive Summary

Lecture 2: Project Management Case Example

Lecture 3: Possible practice: use agile tool

Chapter 11: Part I: Team Building

Lecture 1: Team Building Executive Summary

Lecture 2: Team Building Case Example

Lecture 3: Possible practice: own spider diagram

Chapter 12: Part I: Analytics

Lecture 1: Analytics Executive Summary

Lecture 2: Analytics Case Example

Lecture 3: Possible practice: analyse Kaggle survey data

Chapter 13: Part I: Enterprise Architecture

Lecture 1: Enterprise Architecture Executive Summary

Lecture 2: Enterprise Architecture Case Example

Lecture 3: Possible practice: Own overview of competence model

Chapter 14: Part I: Process Modeling

Lecture 1: Process Modeling Executive Summary

Lecture 2: Process Modeling Case Example

Chapter 15: Part I: Decision Making

Lecture 1: Decision Making Executive Summary

Lecture 2: Decision Making Case Example

Chapter 16: Part I: Artificial Intelligence

Lecture 1: Artificial Intelligence Executive Summary

Lecture 2: Artificial Intelligence Case Example

Lecture 3: Possible practice: embed AI services in your workflow

Chapter 17: Part I: Causality

Lecture 1: Causality Executive Summary

Lecture 2: Causality Case Example

Lecture 3: Possible practice: your sequence and dependencies of topics

Chapter 18: Part I: Summary

Lecture 1: Summary

Chapter 19: Part II: Intro

Lecture 1: The new world of generative AI assistance

Chapter 20: Part II: Introduction and use cases generative AI

Lecture 1: An overview of the generative AI

Lecture 2: Use Cases of generative AI

Chapter 21: Part II: Build Your Own Avatar

Lecture 1: Build your own Avatar

Chapter 22: Part II: Prompt Engineering

Lecture 1: Short Introduction OpenAI

Lecture 2: Prompt Design & Engineering Introduction

Lecture 3: Prompt Design: Building a Supply Chain Graph

Lecture 4: Prompt Design: Optical Character Recognition

Chapter 23: Part II: Using Embedded Generative AI for Work Acceleration

Lecture 1: Generative AI powerd slide/ presentation generation

Instructors

Frank Kienle
Head of Data Science, Digital Strategy Manager

Rating Distribution

1 stars: 0 votes
2 stars: 4 votes
3 stars: 9 votes
4 stars: 29 votes
5 stars: 25 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

Menu