1:1 Executive Crash Course: Data Science, Ki & Python in just one day!

This course provides a comprehensive overview of the core vocabulary and methods of data science, data analysis, and machine learning.

1 day – 1:1 Intensive program – Only for managers, area managers, managing directors and C-level

Data science is a fast-spreading field that combines statistical analysis, data management, and automation with the goal of improving decision-making in business, administration, administration, law, and almost any other area.

One of the most important challenges for decision makers and managers is to understand what constitutes data science and how the insights from this area should be used in assessment and decision-making. In this context, however, it is also important to recognize the extent to which data science, know-how and expertise as well as resources in our own company will be needed in the future – and which projects are suitable for the start, for example. No easy task without deeper knowledge! With this coaching you go one step further.

The focus of this personal intensive course is on case studies with real applications from many areas of the economy. You will also be familiarized with the concepts of data science and learn how to evaluate quantitative evidence and how to design new use cases in the company with data and data science tools. Especially in this context, you will also learn the basics of the data science programming language Python on this day and even apply it to a test case! After that, you're fitter in the subject than 98% of the executives in your industry!

  • 6-8 hours / 1 day crash course at YOU in the office
  • All about data science, artificial intelligence, machine learning and their application
  • You will learn Python in its basic features incl. own application
  • You determine the date!
  • Only for executives, C-levels, Area Managers, Managing Directors

Agenda contents of the 1:1 Excutive Session: Data Science, AI, Machine Learning, Python

  • The vocabulary of the data
  • Creating data: From the raw version to the structured information
  • Beyond spreadsheets: data and databases
  • Real cases from business – presented and explained
  • Core concepts in statistical methods
  • Everything you've always wanted to know about machine learning
  • Descriptive statistics and understanding of variance
  • Programming language Python: Theory and own application in practice
  • Power Session: Development and evaluation of fields of action in your own organization

In a nutshell

  • 6-8 hours / 1 day crash course at YOU in the office
  • Everything about data science, machine learning and its application
  • You will learn Python in its basic features incl. own application
  • You determine the date!
  • Only for executives, C-levels, Area Managers, Managing Directors

What do you get from it?

  • In the future, you will be able to have a say, you will have your own image of "Data Science". You have an initial plan of what data science means to you, your team, and your business. Don't let anything fool you!

In detail:

  • A comprehensive understanding of the core concepts and methods of data science, including data management, data analysis, machine learning, and statistical learning.
  • The ability to evaluate evidence from statistical learning and data science to make informed decisions.
  • Practical and applied knowledge through case studies of a practitioner in one or more of these areas.
  • Basic knowledge (actively applied) in the Python programming language.

Your coach: Kai Schmidhuber

After top executive positions at LOREAL (Chief Digital Officer), HENKEL, DHL (Vice President) and FRAPORT (Senior Vice President), as a digital transformer, it is my passion to help companies reinvent themselves. My mission: digitally demystify! I work without buzzwords and I'm not one of the "magicians" who make the digital world a secret science. With me you get clear text and input that will take you and your company forward here today. And I know what I'm talking about. Because I have already implemented each and every one of my recommendations myself or accompanied them in their consequences. I bring in more than thirteen years of professional experience "with rolled up sleeves" and combine this with the entrepreneurial spirit of four successful start-up sstart-ups. As a keynote speaker with more than 60 appearances in 2019, I know how to convey content in an entertaining, target-group-oriented and instructive way. Motivational boost guaranteed!

Why am I the right coach for data science? As Chief Digital Officer for LOREAL – the global beauty market leader – I have set up the division and the data SCIENCE "from Scratch" team in Germany. From organizational development and recruitment to the identification of application areas and the professional implementation of cross-functional projects as well as the creation of worldwide best practices. I learned a lot, got it wrong and tried it. I would like to share this fresh knowledge of strategy and methods. with them!

Info: What is Python?

With the advent of topics such as data science and machine learning, you also hear the term "Python" again and again. Actually an old hat, because the programming language, which was by the way named after "Monty Python", dates back to 1990. And yet it is more relevant these days than ever. And not only for developers, but also for you! Since its first publication in 1990, Python has found public support in science and business. The programming language is used intensively in artificial intelligence and machine learning and serves as the basis for many cloud applications. This extensibility makes Python an ideal programming language for up-and-coming developers. Due to its scalability, it is also widely used for real-world applications.

Python is a programming language, also known as a scripting language. It differs from other programming languages because it puts maximum emphasis on so-called "code readability". Think of it this way: While other programming languages look more like Egyptian hieroglyphics, Python resembles an SMS one-liner. Highly simplified, of course. Even I can read it. This simplicity makes Python so special and, in my view, has a competitive advantage that is worth gold in the company: the clear code allows developers to spend more time thinking about the real problem they are trying to solve. You need to spend less time thinking about language complexities or decrypting someone else's code.

The simplest use case for Python is automation. Simply put, it can make your work easier. For example, you work in marketing or controlling. And every month you have a certain routine work to do. Numbers. Or e-commerce KPI. Or both. You get a file, you have to link it to a lot of other files and use it to perform an elaborate analysis. Excel sends greetings. Then you should learn Python. Once everything is programmed, you can put your feet up – your process is automated. But this is just the tip of the iceberg of the use of this language.

You can create both command-line and cross-platform applications with Python and deploy them as stand-alone executables. Data science, the scientific data analysis, has become one of the most important use cases of Python. The vast majority of "libraries" used for data science or machine learning have Python interfaces. What are libraries? Think of them as digital libraries with formula collections for programmers. Python's standard library offers modules for common programming tasks, from mathematical computational operations and string processing to multi-process management. Sounds complicated, but it's not.

What's more exciting is that Python treats all elements of the language as an object, including the Python modules and libraries themselves. What's the point? This allows Python to work as a highly efficient code generator. And with that you can even write applications that manipulate their own functions. This type of self-manipulation is really a big advantage, because it makes intelligent functional sequences possible. You can use it to develop a smart, self-learning application. An artificial intelligence.

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