- Keras (Neural Network Library)
- Transformers
- LLMs
- PyTorch (Machine Learning Library)
- Deep Learning
- Artificial Intelligence
- Neural Networks
July 8, 2023
Approximately 4 months at 10 hours a week to completeLINDA KOVACS's account is verified. Coursera certifies their successful completion of IBM IBM AI Engineering Specialization.
Course Certificates Completed
Machine Learning with Python
Introduction to Deep Learning & Neural Networks with Keras
AI Capstone Project with Deep Learning
Deep Learning with Keras and Tensorflow
Introduction to Computer Vision and Image Processing
Introduction to Neural Networks and PyTorch
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: SAEED AGHABOZORGI & Joseph Santarcangelo
Completed by: LINDA KOVACS by June 14, 2023
5-6 weeks of study, 3-6 hours per week
IBM
Taught by: Alex Aklson
Completed by: LINDA KOVACS by June 25, 2023
2 - 3 hours/week
IBM
Taught by: Alex Aklson & Joseph Santarcangelo
Completed by: LINDA KOVACS by July 8, 2023
IBM
Taught by: Samaya Madhavan, Ricky Shi, Alex Aklson, Romeo Kienzler, Joseph Santarcangelo, Wojciech 'Victor' Fulmyk & JEREMY NILMEIER
Completed by: LINDA KOVACS by July 4, 2023
7 weeks of study, 3-4 hours per week
IBM
Taught by: Aije Egwaikhide & Joseph Santarcangelo
Completed by: LINDA KOVACS by July 2, 2023
6 weeks of study, 3-4 hours/week (Approximately 15 hours to complete)
IBM
Taught by: Joseph Santarcangelo
Completed by: LINDA KOVACS by July 2, 2023
6 weeks of study, 2-3 hours/week