- Keras (Neural Network Library)
- Transformers
- LLMs
- PyTorch (Machine Learning Library)
- Deep Learning
- Artificial Intelligence
- Neural Networks
September 20, 2023
Approximately 4 months at 10 hours a week to completeTejas Kamble'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: Tejas Kamble by February 7, 2023
5-6 weeks of study, 3-6 hours per week
IBM
Taught by: Alex Aklson
Completed by: Tejas Kamble by February 13, 2023
2 - 3 hours/week
IBM
Taught by: Alex Aklson & Joseph Santarcangelo
Completed by: Tejas Kamble by September 20, 2023
IBM
Taught by: Samaya Madhavan, Ricky Shi, Alex Aklson, Romeo Kienzler, Joseph Santarcangelo, Wojciech 'Victor' Fulmyk & JEREMY NILMEIER
Completed by: Tejas Kamble by September 19, 2023
7 weeks of study, 3-4 hours per week
IBM
Taught by: Aije Egwaikhide & Joseph Santarcangelo
Completed by: Tejas Kamble by May 20, 2023
6 weeks of study, 3-4 hours/week (Approximately 15 hours to complete)
IBM
Taught by: Joseph Santarcangelo
Completed by: Tejas Kamble by September 19, 2023
6 weeks of study, 2-3 hours/week