- Keras (Neural Network Library)
- Transformers
- LLMs
- PyTorch (Machine Learning Library)
- Deep Learning
- Artificial Intelligence
- Neural Networks
August 31, 2022
Approximately 4 months at 10 hours a week to completeMuhammad Yaseen's account is verified. Coursera certifies their successful completion of IBM IBM AI Engineering Specialization.
Course Certificates Completed
Introduction to Neural Networks and PyTorch
Deep Learning with Keras and Tensorflow
AI Capstone Project with Deep Learning
Introduction to Computer Vision and Image Processing
Machine Learning with Python
Introduction to Deep Learning & Neural Networks with Keras
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: Joseph Santarcangelo
Completed by: Muhammad Yaseen by July 25, 2022
6 weeks of study, 2-3 hours/week
IBM
Taught by: Samaya Madhavan, Ricky Shi, Alex Aklson, Romeo Kienzler, Joseph Santarcangelo, Wojciech 'Victor' Fulmyk & JEREMY NILMEIER
Completed by: Muhammad Yaseen by August 30, 2022
7 weeks of study, 3-4 hours per week
IBM
Taught by: Alex Aklson & Joseph Santarcangelo
Completed by: Muhammad Yaseen by August 31, 2022
IBM
Taught by: Aije Egwaikhide & Joseph Santarcangelo
Completed by: Muhammad Yaseen by July 1, 2022
6 weeks of study, 3-4 hours/week (Approximately 15 hours to complete)
IBM
Taught by: SAEED AGHABOZORGI & Joseph Santarcangelo
Completed by: Muhammad Yaseen by July 1, 2022
5-6 weeks of study, 3-6 hours per week
IBM
Taught by: Alex Aklson
Completed by: Muhammad Yaseen by July 1, 2022
2 - 3 hours/week