- 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
April 17, 2020
Approximately 2 months at 10 hours a week to completeRakshita Mathur's account is verified. Coursera certifies their successful completion of IBM IBM AI Engineering Specialization.
Course Certificates Completed
Deep Neural Networks with PyTorch
Machine Learning with Python
Introduction to Deep Learning & Neural Networks with Keras
Scalable Machine Learning on Big Data using Apache Spark
Building Deep Learning Models with TensorFlow
AI Capstone Project with Deep Learning
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: Rakshita Mathur by April 17, 2020
IBM
Taught by: SAEED AGHABOZORGI & Joseph Santarcangelo
Completed by: Rakshita Mathur by March 30, 2020
5-6 weeks of study, 3-6 hours per week
IBM
Taught by: Alex Aklson
Completed by: Rakshita Mathur by April 12, 2020
2 - 3 hours/week
IBM
Taught by: Romeo Kienzler
Completed by: Rakshita Mathur by April 11, 2020
IBM
Taught by: Samaya Madhavan, Ricky Shi, Alex Aklson, Romeo Kienzler, Joseph Santarcangelo, JEREMY NILMEIER & IBM Skills Network Team
Completed by: Rakshita Mathur by April 16, 2020
7 weeks of study, 2–3 hours per week
IBM
Taught by: Alex Aklson & Joseph Santarcangelo
Completed by: Rakshita Mathur by April 17, 2020