- Keras (Neural Network Library)
- Transformers
- LLMs
- PyTorch (Machine Learning Library)
- Deep Learning
- Artificial Intelligence
- Neural Networks
January 18, 2024
Approximately 4 months at 10 hours a week to completeElizabeth Makayed's account is verified. Coursera certifies their successful completion of IBM IBM AI Engineering Specialization.
Course Certificates Completed
AI Capstone Project with Deep Learning
Deep Learning with Keras and Tensorflow
Machine Learning with Python
Introduction to Deep Learning & Neural Networks with Keras
Introduction to Neural Networks and PyTorch
Introduction to Computer Vision and Image Processing
Describe machine learning, deep learning, neural networks, and ML algorithms like classification, regression, clustering, and dimensional reductionÂ
Implement supervised and unsupervised machine learning models using SciPy and ScikitLearnÂ
Deploy machine learning algorithms and pipelines on Apache SparkÂ
Build deep learning models and neural networks using Keras, PyTorch, and TensorFlowÂ
Earned after completing each course in the Specialization
IBM
Taught by: Alex Aklson & Joseph Santarcangelo
Completed by: Elizabeth Makayed by January 16, 2024
IBM
Taught by: Samaya Madhavan, Ricky Shi, Alex Aklson, Romeo Kienzler, Joseph Santarcangelo, Wojciech 'Victor' Fulmyk & JEREMY NILMEIER
Completed by: Elizabeth Makayed by January 14, 2024
7 weeks of study, 3-4 hours per week
IBM
Taught by: SAEED AGHABOZORGI & Joseph Santarcangelo
Completed by: Elizabeth Makayed by December 27, 2023
5-6 weeks of study, 3-6 hours per week
IBM
Taught by: Alex Aklson
Completed by: Elizabeth Makayed by December 31, 2023
2 - 3 hours/week
IBM
Taught by: Joseph Santarcangelo
Completed by: Elizabeth Makayed by January 12, 2024
6 weeks of study, 2-3 hours/week
IBM
Taught by: Aije Egwaikhide & Joseph Santarcangelo
Completed by: Elizabeth Makayed by January 6, 2024
6 weeks of study, 3-4 hours/week (Approximately 15 hours to complete)