- Machine Learning
- Deep Learning
- Artificial Neural Networks
- Human Learning
- Python Programming
- Machine Learning Algorithms
- Applied Machine Learning
- Algorithms
- Regression
- Network Model
- Computer Vision
- Computer Programming
July 8, 2024
Approximately 2 months at 10 hours a week to completeSudhanshu Kaushik's account is verified. Coursera certifies their successful completion of IBM IBM AI Engineering Specialization.
Course Certificates Completed
Machine Learning with Python
Introduction to Computer Vision and Image Processing
AI Capstone Project with Deep Learning
Building Deep Learning Models with TensorFlow
Deep Neural Networks with PyTorch
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: SAEED AGHABOZORGI & Joseph Santarcangelo
Completed by: Sudhanshu Kaushik by July 5, 2024
5-6 weeks of study, 3-6 hours per week
IBM
Taught by: Aije Egwaikhide & Joseph Santarcangelo
Completed by: Sudhanshu Kaushik by July 7, 2024
6 weeks of study, 3-4 hours/week (Approximately 15 hours to complete)
IBM
Taught by: Alex Aklson & Joseph Santarcangelo
Completed by: Sudhanshu Kaushik by July 8, 2024
IBM
Taught by: Samaya Madhavan, JEREMY NILMEIER, Romeo Kienzler & Alex Aklson
Completed by: Sudhanshu Kaushik by July 7, 2024
4-5 hours/week
IBM
Taught by: Joseph Santarcangelo
Completed by: Sudhanshu Kaushik by July 7, 2024
IBM
Taught by: Alex Aklson
Completed by: Sudhanshu Kaushik by July 6, 2024
2 - 3 hours/week