Course Information

  • Sessions 1 day
  • Duration 7.5 hrs
  • Level Intermediate
  • Assessment NA

Venue

Download Course Brochure

Certification

  • Certificate of Completion from Tertiary Courses - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Courses.

Basic Generative Adversarial Network (GAN) Training

Course Code: C1043

What's This Course About

Embark on a transformative journey into the foundational and advanced realms of Generative Adversarial Networks (GANs) with our meticulously curated training at Tertiary Courses. Starting with a robust understanding of the Basic GAN Framework, participants are gradually introduced to the intricacies and nuances of this groundbreaking AI technology.

Delving deeper, the training unravels the layers behind DCGAN, WGAN, and the highly intriguing Conditional GAN. These advanced modules ensure participants grasp the holistic view of GANs, empowering them with the expertise to develop sophisticated AI models. This course is the key to unlocking the immense potential and creativity that GANs offer in the realm of artificial intelligence.

WSQ Funding

Full Fee ₵4,200.00 Before GST
GST ₵378.00 9% of fee
Baseline Nett ₵2,478.00 SG/PR age 21+ · 50% funded
MCES / SME Nett ₵1,638.00 SG age 40+ · 70% funded
Funding and Grant Applications

No funding is available for this course

For WSQ funding, please checkout the details at NICF - Computational Modeling with Generative Adversarial Network (GAN)

Course Fee

₵4,200.00

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

Post-Course Support

  • We provide free consultation related to the subject matter after the course.
  • Please email your queries to info@tertiarycourses.com.gh and we will forward your queries to the subject matter experts and get back to you as soon as possible.

Cancellation & Reschedule Policy

  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
  • Note: the venue of the training is subject to changes due to class size and availability of the classroom. The minimum class size to start a class is 3 Pax.

Course Details

Course Details

What You'll Learn

Topic 1 Overview Generative Adversarial Network (GAN)

  • Introduction to GAN
  • GAN Framework

Topic 2 Key GAN Algorithms

  • Deep Convolutional GAN (DCGAN)
  • Wasserstein GAN (WGAAN)
  • Conditional GAN (CGAN

Course Info

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions
  • Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

  • Positive Learning Attitude
  • Enthusiastic Learner

Experience

  • Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

Hardware: Window or Mac Laptops

Job Roles

Job Roles

  • Data Scientist
  • Machine Learning Engineer
  • AI Researcher
  • Deep Learning Specialist
  • Computer Vision Engineer
  • AI Product Developer
  • Graphics Software Developer
  • Multimedia Artist (using AI)
  • Bioinformatics Researcher (for GAN-based simulations)
  • Financial Modeler (using AI for simulations)
  • R&D Specialist in AI
  • Robotics Engineer (with AI modeling)
  • Game Developer (using GANs for content generation)
  • Innovation Manager (in tech firms)
  • Computational Scientist

Trainers

Trainers

is an accomplished IT and data specialist with over 20 years of experience in academia, ICT leadership, and professional training, with a strong focus on data analytics and Excel-based solutions. He has developed and delivered specialized training programs on Statistical Data Analysis with Excel and Visual Basic for Applications (VBA) for Excel, equipping learners with advanced data manipulation, automation, and reporting skills. His expertise extends to automating institutional reporting systems, where he successfully streamlined academic records management through Excel-based tools, integrating macros and automation to improve efficiency and accuracy. As a trainer and consultant, Dr. Siraj has taught Excel to diverse audiences, including university staff, administrative teams, and professionals in banking, security, and education, ensuring they can apply Excel for decision-making, statistical modeling, and process automation. His practical mastery of Excel is complemented by his deep knowledge of office automation and ICT project management, making him a highly sought-after trainer in data analysis and productivity tools. With his blend of hands-on technical expertise and instructional experience, Dr. Siraj stands out as a credible authority in leveraging Excel to drive organizational efficiency and data-driven strategies

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