12 WEEKS
VIRTUAL &
PHYSICAL
PROJECTS/
ASSIGNMENTS
CERTIFICATION
What You’ll Learn
By the end of this course, you will:
- Understand the core principles of AI and Machine Learning, including supervised and unsupervised learning.
- Build, train, and deploy models using industry-standard tools like Python, TensorFlow, and AWS SageMaker.
- Develop solutions in areas such as natural language processing (NLP) and computer vision (CV).
- Explore advanced concepts like neural networks, ensemble learning, and transfer learning.
- Integrate AI models into web applications and business intelligence platforms.
₦250,000
Why Enroll?
Artificial Intelligence (AI) is revolutionizing industries, creating opportunities, and driving innovation. At Ibadan Digital Academy, our 12-week AI curriculum is designed to provide you with in-depth knowledge and practical expertise in AI and Machine Learning (ML). From foundational concepts to advanced applications like neural networks, natural language processing, and computer vision, this program equips you to build impactful AI solutions and thrive in a competitive global marketplace.
Practical Learning:
Weekly hands-on activities and a capstone project provide real-world experience.
Future-Focused:
Master advanced AI concepts like transfer learning and AI explainability.
Industry Applications:
Explore AI use cases in finance, healthcare, and business intelligence.
Career Support:
Receive resume reviews, interview preparation, and career guidance.
Global Standards:
Learn with tools and frameworks aligned to industry best practices.
Artificial Intelligence Course Outline
Week 1: Introduction to AI and Machine Learning
- Understand the history, evolution, and applications of AI.
- Set up Python and Jupyter Notebook for AI/ML projects.
- Learn the basics of supervised, unsupervised, and reinforcement learning.
Week 2: Fundamentals of Machine Learning
- Explore key ML algorithms, including Linear Regression and Decision Trees.
- Understand applications of ML in healthcare, finance, and marketing.
- Build basic models using scikit-learn.
Week 3: AI Systems and Applications
- Learn the structure of neural networks and key mathematical concepts for ML.
- Explore real-world AI applications across industries.
- Implement a simple neural network in Keras.
Week 4: Python Programming for Machine Learning
- Master Python libraries like NumPy, Pandas, and Matplotlib for AI.
- Build regression models and visualize data.
- Understand the importance of model explainability in AI.
Week 5: Data Preprocessing and Sentiment Analysis
- Clean, normalize, and preprocess datasets.
- Perform sentiment analysis using pre-trained models and NLP techniques.
Week 6: Advanced AI and Emerging Trends
- Learn about ensemble learning methods like Bagging and Boosting.
- Explore NLP advancements and AI applications in computer vision.
- Use AWS SageMaker for model deployment.
Week 7: Supervised Learning and Web Development
- Dive into classification techniques like Random Forest and SVM.
- Develop AI-powered web applications using Flask.
- Deploy supervised models into simple web interfaces.
Week 8: Mathematics for Machine Learning and Unsupervised Learning
- Apply concepts like linear algebra and PCA in ML.
- Build clustering models and perform dimensionality reduction.
Week 9: Ensemble Learning and Machine Learning Security
- Understand techniques like Stacking, Random Forest, and AdaBoost.
- Address ML security challenges and mitigate adversarial threats.
Week 10: Deep Learning Fundamentals
- Build neural networks for image classification and time-series analysis.
- Explore advanced methods like transfer learning and hyperparameter tuning.
- Implement deep learning models using TensorFlow and PyTorch.
Week 11: AI for Business Intelligence and Capstone Preparation
- Integrate AI insights into Power BI dashboards.
- Define the scope of your capstone project and prepare datasets.
Week 12: Capstone Project Presentation
- Develop and showcase a real-world AI solution.
- Present your project to peers and instructors, receiving valuable feedback.
Tools Covered
