AI and Machine Learning Skills Certificate

Learning Path: AI and Machine Learning Skills Certificate

  • Introduction to AI, Robotics and Data 
  • Global Impact of AI 
  • Python for Everyone 
  • Introduction to Data Analysis 
  • Machine Learning 

Introduction to AI, Robotics and Data 

Digital and AI technologies are conquering and fundamentally changing our world with an amazing speed. And they will increasingly have a very significant impact on all aspects of our life, our economy, our entire society.

From voice assistants and chatbots to self-driving cars and humanoid robots, these technologies improve efficiency and quality of life and open up totally new opportunities to create positive value. Therefore, we should all learn how to make good use of these new opportunities but also how to avoid the pitfalls, risks and threats which are also inevitably related to AI.

With this unique introductory course you will get: 

  • a comprehensive 360º overview of all relevant topics regarding AI
  • a basic understanding of AI  
  • an overview of the most relevant AI technologies

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Global Impact of AI

The "Global Impact of AI" course is specifically designed to help you explore the impact of Artificial Intelligence, AI, and digitalization on our society and all of us. It offers you a global perspective on the fascinating opportunities but also ethical aspects, risks and threats which are inevitably associated with AI and shares insights on the very different roles humans and machines will have in the long term.

With this introductory course you will discover:

  • AI-related risks and opportunities for our society and all of us 
  • Ethical challenges and AI regulation
  • The long-term roles of humans vs. machines 
  • The current state of global AI competition and collaboration

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Python for Everyone

This course is for everyone who wants to take the first step to the Artificial Intelligence and Data Science world by learning one of the most popular programming languages from scratch.

By participating in this education series that we have created for you using real-world experiences, you will have taken the first step into the world of programming and artificial intelligence.

With this Course, you will gain the following competencies:

  • Primitive Data Types and Data Collections
  • Loops and Conditional Statements,
  • Functional Programming, 
  • Exception Handling, 
  • Data Analysis & Manipulation

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Introduction to Data Analysis (coming soon)

Data is the most important element of machine learning projects and they are found in raw format in real life. With this course, you will learn how to analyze and process raw data. Data needs to be prepared for machine learning models. What we mean by the preparation of data covers topics such as cleaning, determining statistics, eliminating deficiencies and visualizing. You will have all of these competencies in the well-prepared data analysis course. By using the Python programming language, you will be able to provide very fast and high level analysis even on large data.

With this Course, you will gain the following competencies:

  • Exploratory Data Analysis
  • Elements of Structured Data
  • Data Distribution, Correlations, Plotting and Visualization Techniques
  • Data Bias, Statisticals Tests, Data Manipulation with Pandas, 
  • Data Visualization with Seaborn

Machine Learning

This course, which contains all the basic content you need to learn in the Introduction to Data Science, aims to evolve you into a good machine learning practitioner. Machine learning forms the core of data science, one of the most popular professions of our age. With this course, you will develop a high level of knowledge and deep understanding of data. It is anticipated that a good grasp of data, which is beginning to surround us, and ability to analyze will be the most important competence of the future. This education has been prepared carefully to evolve you for the upcoming data age.

With this Course, you will gain the following competencies:

  • Linear Algebra and Probability
  • Data Preparation, Regularization
  • Supervised and Unsupervised Learning, 
  • Linear & Logistic Regression and Decision Algorithms
  • Data Modeling and Creating Machine Learning Models.

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