Deep Learning (ML II)
Micro-DegreeOnline

Deep Learning (ML II)

Book NowGet in Touch

Program Details

  • Language: English
  • Fees: €900
  • Study Mode: Full-time / Part-time
  • Registration Deadline: 30th September 2027
  • Entry requirements:
    • High school diploma or equivalent
    • Basic computer literacy
    • English Level B1 (CEFR) or equivalent

Study Access

Pay for one quarter and have access to the learning materials for 6 months, with the option to extend access if needed.

Program Coordinator

Prof. Dr. Raad Bin Tareaf
Prof. Dr. Raad Bin Tareaf

About This Course

In this module, students learn how to interpret, modify, and design deep learning architectures. We analyze structural layers, activation functions, and optimization pathways, establishing a classification of architectural principles to solve real-world problems.

A central focus is understanding network training mechanics, hyperparameter optimization, and sequence processing using advanced self-learning principles.

Learning Objectives

By the end of this course, students will be able to:

  • Analyze the paradigm shift from classical machine learning to deep neural networks and identify where classical techniques fall short.
  • Construct and configure core components of Deep Neural Networks, including input, hidden, and output layers.
  • Implement optimization techniques, including backpropagation, evaluation metrics, and hyperparameter tuning.
  • Develop Convolutional Neural Networks (CNNs) utilizing filters, kernels, and pooling layers for visual data tasks.
  • Build Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM &BI_LSTM) networks for univariate and multivariate time-series forecasting.
  • Evaluate Transformer models by understanding their history, structural internals, and multi-head self-attention mechanisms.

Requirements

Students should have prior knowledge of basic machine learning concepts, proficiency in Python, and familiarity with foundational deep learning techniques. Experience with frameworks like TensorFlow or PyTorch is recommended but not required.

General Information

  • Teaching Format: Experience
  • Total Workload Master: 125h (40h/85h) / 5 ECTS
  • Total Workload MBA: 100h (40h/60h) / 4 ECTS
  • Total Workload Micro Degree: 125h (40h/85h) / Equivalent to 5 ECTS
  • Module coordinator: Prof. Dr. Raad Bin Tareaf
  • Examinations: Quizzes, presentation(s), essay(s)/paper(s), project report(s), written exam (tbd) - Details will be announced with course start.
  • Offered: Even quarters

Frequently Asked Questions

German UDS offers a range of cutting-edge digital programs in MBA, Master’s Programs and Micro-Degree Programs. Please refer to our University’s Study program page for further details.

Micro-Degree Programs:
- No specific requirements
Master’s Programs:
- Bachelor’s degree in a relevant field with a minimum grade of 2.5 (German system) or equivalent
- English: Minimum B2
Additional requirements may apply (e.g., work experience for MBA & M.A. programs). Visit our admissions page for full details.

For our study programs you can apply as follows:

  • Micro-Degree Programs:
    Micro-Degree programs can be booked directly on our Micro-Degree page. Simply browse our available Micro-Degrees and enroll immediately without any application process.
  • MBA and Master’s Programs:
    01 Register/Login
    Begin by creating an account.
    After creating a new account, you’ll receive an email with a verification link. Click the link to verify your email address before proceeding.
    If you already have an account, simply log in to continue.
    02 Start Your Application
    After filling out the form, be sure to check your email. You will receive a message from us containing a direct link to start your application.
    Go to the “Start your Application!” and begin your application journey.
    Note: This option becomes available only after completing the registration and login.

MBA programs: €7,500 per year
Master’s programs: €7,500 per year
Micro-Degrees: €900 per program
For full details, visit the official admissions page.

Reliable high-speed internet connection
Computer (Windows or Mac) with webcam and microphone

Student life at German UDS is designed for maximum flexibility, enabling learners to study anytime, anywhere, and at their own pace. Whether enrolling in a free course or a full degree program, students have full access to online course materials and complete assignments within set deadlines, making it easy to balance education with personal and professional commitments. In addition to academic flexibility, students also enjoy a vibrant virtual campus experience through COVE – our Campus of Virtual Education. COVE provides an immersive digital environment where students can hang out in virtual spaces like the cafeteria, lounge, or library. It’s a place to connect, chat, and build friendships beyond the classroom. Regular online events, social gatherings, and themed meetups offer students opportunities to network, collaborate, and be part of a supportive international community.