Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
13 Hour(s) 27 Minute(s)
Language
English
Taught by
School of AI
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
1 views
Course Overview
Master AI Engineering: Build, Train, and Deploy Scalable AI Solutions with Real-World Projects and Hands-On Learning.(AI
Welcome to the AI Engineering Masterclass: From Zero to AI Hero! This comprehensive AI course is designed to take you on an exciting journey from an AI beginner to a confident AI Engineer, equipped with the skills to build, train, and deploy Artificial Intelligence solutions. Whether you're starting from scratch or looking to solidify your AI expertise, this AI Masterclass provides the step-by-step roadmap you need to succeed.
In this AI Engineering Masterclass, you'll begin with the foundations of AI, exploring Python programming, data preprocessing, and the basics of machine learning. As you progress, you'll dive into advanced AI topics such as neural networks, deep learning, natural language processing (NLP), and computer vision. You’ll also gain hands-on experience with cutting-edge AI frameworks like TensorFlow, PyTorch, and Hugging Face to create production-ready AI solutions.
This AI Masterclass emphasizes practical AI skills, with real-world projects embedded into every module. You'll learn to tackle real business problems using AI technologies, optimize AI models, and deploy scalable solutions.
Why Choose the AI Engineering Masterclass?
Beginner-Friendly AI Curriculum: Start from scratch and grow into an expert
Hands-On AI Projects: Build real AI applications for real-world challenges
Master AI Frameworks: Learn TensorFlow, PyTorch, and Hugging Face
Comprehensive AI Training: Cover Python, Machine Learning, Deep Learning, NLP, and AI Deployment
Zero to AI Hero Roadmap: Structured learning path for complete AI mastery
By the end of this AI Engineering Masterclass, you'll not only have mastered AI engineering skills, but you'll also be equipped to innovate, lead AI projects, and drive transformation with AI solutions in your organization or startup.
Whether you're an aspiring AI Engineer, an AI enthusiast, or someone looking to break into the Artificial Intelligence industry, this AI Masterclass is your ultimate resource to go From Zero to AI Hero.
Join the AI Revolution Today – Enroll in the AI Engineering Masterclass: From Zero to AI Hero and take the first step towards mastering AI!
Course Content
- 14 section(s)
- 106 lecture(s)
- Section 1 Introduction to Course
- Section 2 Week 1: Python Programming Basics
- Section 3 Week 2: Data Science Essentials
- Section 4 Week 3: Mathematics for Machine Learning
- Section 5 Week 4: Probability and Statistics for Machine Learning
- Section 6 Week 5: Introduction to Machine Learning
- Section 7 Week 6: Feature Engineering and Model Evaluation
- Section 8 Week 7: Advanced Machine Learning Algorithms
- Section 9 Week 8: Model Tuning and Optimization
- Section 10 Week 9: Neural Networks and Deep Learning Fundamentals
- Section 11 Week 10: Convolutional Neural Networks (CNNs)
- Section 12 Week 11: Recurrent Neural Networks (RNNs) and Sequence Modeling
- Section 13 Week 12: Transformers and Attention Mechanisms
- Section 14 Week 13: Transfer Learning and Fine-Tuning
What You’ll Learn
- Build AI models using Python, TensorFlow, and PyTorch to create intelligent systems capable of solving real-world problems
- Preprocess, clean, and analyze complex datasets to ensure high-quality input for machine learning and AI model training
- Train, evaluate, and optimize machine learning models for tasks like regression, classification, and clustering
- Design, implement, and fine-tune neural networks, including CNNs and RNNs, for advanced AI applications
- Apply Natural Language Processing (NLP) techniques to analyze, interpret, and generate human-like text data
- Leverage transfer learning to adapt pre-trained AI models for new tasks, reducing development time and resources
- Deploy AI models using scalable APIs and containerization tools like Docker for seamless integration into applications
- Monitor AI model performance, detect data drift, and establish retraining workflows for consistent reliability
- Solve real-world business and technical challenges using AI-driven approaches and intelligent systems
- Develop end-to-end AI projects, from ideation and prototyping to deployment and long-term maintenance
Skills covered in this course
Reviews
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SSetai Teboho Martin Rapontso
I like what I am learning here.
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AAna - Maria Lemnaru
cmd lines not correct should indicate python3 & pip3 for some of us like me.... the path was not automatically updated on my mac so needed to do manually for python and also for jupyter so please indicate how to check it and install it
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AAnbananthan Perumal
Marvelous and excellent training. Thanks
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SSteve Dubinsky
I come in with experience - this early lecture is not informative to me, but I appreciate that the concepts are presented well and would be helpful to someone who is a beginner or new to the Python language.
