AI, Machine Learning & Deep Learning Essentials Training in Germany

  • Learn via: Classroom
  • Duration: 2 Days
  • Price: From €2,983+VAT
We can host this training at your preferred location. Contact us!

Explore AI, ML and DL Differences, Advantages, Modern Uses. Techniques for Adoption, Tools, Algorithm's and More

Introduction to AI, Machine Learning & Deep Learning Essentials is an engaging, hands-on training program designed to provide students new to these areas with a baseline understanding of the core technologies, skills, business application and tools surrounding them. These fast growing, critical technologies are currently shaping the future of IT, development and analytics.

This program combines hands-on machine-based labs, live demonstrations and discussions that explore current trends, tools and skills, as well as advances in these areas. Working in a hands-on manner, attendees will gain a basic understanding of terms, skills and capabilities in this technology stack, providing them with a solid foundation for next-step learning as they pursue defined roles in these areas.



Is This The Right Course?

The general pre-requisite items below would be helpful for attendees to familiarize themselves with in order to gain the most from the discussions and hands-on labs work planned for each general related skills area listed below. Students without supporting experience in certain areas can plan to follow along with labs or utilize them as demonstrations.

Some of the related useful skills

  • Required - Enterprise IT / Business Knowledge: Attendees should have some familiarity with Enterprise IT as well as a general (high-level) understanding of systems architecture, as well as some knowledge of the business drivers that might be able to take advantage of applying data science, AI and machine learning.
  • Recommended - Advanced Math / Statistics: Advanced math and essentials statistics knowledge is useful in understanding and working with Algorithms
  • Recommended – Basic Language / Scripting Knowledge: Basic Python (or R) scripting is applicable to machine learning and deep learning. Basic Java is useful for working with some of the advanced tools such as Spark or TensorFlow.

The general pre-requisite items below would be helpful for attendees to familiarize themselves with in order to gain the most from the discussions and hands-on labs work planned for each general related skills area listed below. Students without supporting experience in certain areas can plan to follow along with labs or utilize them as demonstrations.

Some of the related useful skills

  • Required - Enterprise IT / Business Knowledge: Attendees should have some familiarity with Enterprise IT as well as a general (high-level) understanding of systems architecture, as well as some knowledge of the business drivers that might be able to take advantage of applying data science, AI and machine learning.
  • Recommended - Advanced Math / Statistics: Advanced math and essentials statistics knowledge is useful in understanding and working with Algorithms
  • Recommended – Basic Language / Scripting Knowledge: Basic Python (or R) scripting is applicable to machine learning and deep learning. Basic Java is useful for working with some of the advanced tools such as Spark or TensorFlow.

Led by our expert AI / Machine Learning practitioner, students will learn about and explore:

  • The What and Why of AI, Machine Learning & Deep Learning – why is this important and exciting?
  • Getting the Basics: High-level skills, vocabulary and terminology
  • AI, Machine Learning and Deep Learning – what are the differences and uses?
  • Latest trends and research
  • Who’s Using It and to What Advantage?
  • How to adopt AI, ML and DL
  • Hands-on Machine Learning – algorithms, neural networks, natural language processing & more
  • Tools and Languages: Python, R, Spark, TensorFlow, Keras
  • Deep Learning Essentials

Exploring Data Science – The Foundation of AI, Machine Learning & Deep Learning

  • What is Data Science?
  • New Ways of Thinking about and using Data
  • Challenges of processing
  • Technologies
  • Strategies
  • Where does data science fit in?
  • DS ecosystem – AI, Machine Learning, Deep Learning
  • Data and the Scientific Method
  • Data Science vs. Data Engineering
  • Sharing Results with Colleagues
  • Recording experiments
  • The Data Science Team members
  • Data Science Infrastructure
  • Current Tools, Trends & Technologies
  • Applying Data Science to Your Industry

Understanding AI

  • AI - How did we get here?
  • Recent advances in data, hardware
  • Cutting edge research and applications
  • Getting the basics: Core terms and vocabulary

Understanding Machine Learning

  • Who is leveraging this and why
  • Overview of ML – what’s the difference?
  • Related examples of ML algorithms and applications
  • Surrounding tools and technologies: Python and Spark

Machine Learning

  • Supervised vs. Unsupervised
  • Classification
  • Regression
  • Clustering
  • Dimensionality Regression
  • Ensemble Methods

Understanding Deep Learning

  • What is it, and how is this different than AI and ML?
  • Who’s using Deep Learning and Why
  • Deep Learning algorithms and applications
  • Surrounding tools and technologies: Python, TensorFlow, Keras

Expert Systems

  • Rules Systems
  • Feedback loops
  • RETE and beyond
  • Expert Systems in practice

Neural Networks

  • Neural Networks
  • Recurrent Neural Networks
  • Long-Short Term Memory Networks
  • Applying Neural Networks

Natural Language Processing

  • Language and Semantic Meaning
  • Bigrams, Trigrams, and n-Grams
  • Root stemming and branching
  • NLP in the world

Image, Video, and Audio Processing

  • Image processing and Identification
  • Facial Analysis
  • Audio Processing
  • Analyzing Streaming Video
  • Real-world AV processing

Sentiment Analysis

  • Sentiment: The beginnings of emotional understanding
  • Sentiment indicators
  • Sentiment Sampling
  • Algorithmic Trading on Sentiment
  • Predicting Elections

Current Tools of the Trade - AI, ML & DL - Software Ecosystem

  • Python, NumPy, Pandas, SciKit
  • Hadoop and Spark
  • NoSQL Databases
  • TensorFlow, Keras, and NLTK
  • Drools
  • Libraries
  • Cloud offerings

Making it Happen: How to Adopt AI & ML in Enterprises

  • Technology stack
  • Assembling an effective team
  • Process – how does this all come together
  • Best Practices – what do your people need to succeed

Resources – where to find more information

Time Permitting: Capstone Project

  • Hands-on guided workshop utilizing skills learned throughout the course


Contact us for more detail about our trainings and for all other enquiries!

Upcoming Trainings

Join our public courses in our Germany facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

10 Januar 2025 (2 Days)
Berlin, Hamburg, Münih
Classroom / Virtual Classroom
21 Januar 2025 (2 Days)
Berlin, Hamburg, Münih
Classroom / Virtual Classroom
10 Januar 2025 (2 Days)
Berlin, Hamburg, Münih
Classroom / Virtual Classroom
11 Februar 2025 (2 Days)
Berlin, Hamburg, Münih
Classroom / Virtual Classroom
21 Januar 2025 (2 Days)
Berlin, Hamburg, Münih
Classroom / Virtual Classroom
01 März 2025 (2 Days)
Berlin, Hamburg, Münih
Classroom / Virtual Classroom
11 Februar 2025 (2 Days)
Berlin, Hamburg, Münih
Classroom / Virtual Classroom
09 März 2025 (2 Days)
Berlin, Hamburg, Münih
Classroom / Virtual Classroom
AI, Machine Learning & Deep Learning Essentials Training Course in Germany

The Federal Republic of Germany is the second most populous country in Europe and is located in Central Europe. The official language of the country is German. Germany is one of the richest countries in the world. The main exports of the country include motor vehicles and iron and steel products.

Here are some fun facts about Germany:
The fairy tale writer, the Brothers Grimm, came from Germany and wrote many famous stories such as Cinderella, Snow White, and Sleeping Beauty.
Germany is home to the largest theme park in Europe, the Europa-Park.
The famous composer Ludwig van Beethoven was born in Germany.
The Autobahn, the German highway system, is known for having no general speed limit.


Berlin was divided by the Berlin Wall from 1961 to 1989. Known for its street art, Berlin has many colorful murals and graffiti throughout the city. Also, Berlin is home to many famous museums, such as the Pergamon Museum and the Museum Island. Many clubs and bars stay open until the early hours of the morning in this big city.

Another popular city is Munich, which is famous for its Oktoberfest beer festival that attracts millions of visitors every year. Munich is also home to many historic buildings, including Nymphenburg Palace and the Marienplatz town square.

The country's capital and largest city is Berlin, however Frankfurt is considered to be the business and financial center of Germany. It is home to the Frankfurt Stock Exchange, the European Central Bank, and many other financial institutions. Because of its central location within Europe and its status as a major financial hub, Frankfurt is often referred to as the "Mainhattan," a play on the city's name and its association with the Manhattan financial district in New York City.

Frankfurt is also a major transportation hub, with the largest airport in Germany and one of the largest in Europe, Frankfurt Airport. Additionally, it is a popular destination for tourists, with its historic city center, beautiful parks, and vibrant cultural scene.

Some of the top German technology companies like Siemens AG, Bosch, SAP SE, Deutsche Telekom, Daimler AG and Volkswagen has business centers in Frankfurt. The country has a strong tradition of engineering and innovation, and is home to many other world-class technology companies and research institutions.

Tailored to meet the specific needs of Germany, Bilginç IT Academy combines cutting-edge training methodologies with our comprehensive range of Certification Exam preparation courses and accredited corporate training programs. Experience a transformative approach to IT training that will redefine your expectations.
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