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Clem Martins's Blog IBM AI Engineering Professional Certificate
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  • Author Author: clem57
  • Date Created: 3 Jan 2020 3:21 PM Date Created
  • Views 1121 views
  • Likes 2 likes
  • Comments 0 comments
  • coursera
  • ibm
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Recommended

IBM AI Engineering Professional Certificate

clem57
clem57
3 Jan 2020

This Professional Certificate consists of 6 self-paced courses. Effort required to complete each course is 4-5 weeks if spending 2-4 hours per week. At this rate the entire specialization can be completed in 3-6 months.

 

This Professional Certificate pre-requisties the following skills:

  • Working Knowledge of Python Programming language and Jupyter Notebooks e.g. Python for Data Science and AI
  • High School Mathematics or Math for Machine Learning

 

It is highly recommended that you complete either or both of the following Professional Certificates before starting this one:

  • IBM Data Science Professional Certificate
  • IBM Applied AI Professional Certificate

 

SKILLS YOU WILL GAIN

Data ScienceDeep LearningArtificial Intelligence (AI)Machine LearningApache Spark

 

Upon completing this Professional Certificate you will be able to:

  • Describe what is Machine Learning (ML), Deep Learning (DL) & Neural Networks
  • Explain ML algorithms including Classification, Regression, Clustering, and Dimensional Reduction
  • Implement Supervised and Unsupervised ML models using scipy and scikitlearn
  • Express how Apache Spark works and how to perform Machine Learning on Big Data
  • Deploy ML Algorithms and Pipelines on Apache Spark
  • Demonstrate an understanding of Deep Learning models such as autoencoders, restricted Boltzmann machines,  convolutional networks, recursive neural networks, and recurrent networks
  • Build deep learning models and neural networks using the Keras library
  • Utilize the PyTorch library for Deep Learning applications and build Deep Neural Networks
  • Explain foundational TensorFlow concepts like main functions, operations & execution pipelines
  • Apply deep learning using TensorFlow and perform backpropagation to tune the weights and biases
  • Determine what kind of deep learning method to use in which situation and build a deep learning model to solve a real problem
  • Demonstrate ability to present and communicate outcomes of deep learning projects

 

 

To apply:

https://www.coursera.org/professional-certificates/ai-engineer?utm_medium=email&utm_source=marketing&utm_campaign=wLYtAC…

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