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AI ML with Deep Learning and Supervised Models Specialization

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Simplilearn

AI ML with Deep Learning and Supervised Models Specialization

AI, ML, and Deep Learning Simplified

Included with Coursera Plus

Get in-depth knowledge of a subject
Beginner level

Recommended experience

1 month
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Beginner level

Recommended experience

1 month
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Master AI, regression, classification, and clustering techniques

  • Build neural networks with TensorFlow, Keras, RNNs, and LSTMs

  • Understand feedforward, convolutional, and recurrent networks

  • Explore AI ethics, risks, and transformative industry potential

Details to know

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Taught in English
Recently updated!

March 2025

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Simplilearn
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Specialization - 3 course series

What you'll learn

  • Master AI fundamentals, applications, and key machine learning types.

  • Understand neural networks, their types, and real-world applications.

  • Build and deploy neural network models using TensorFlow and Python.

  • Explore AI ethics, risks, and its transformative future potential.

Skills you'll gain

Category: Neural Networks
Category: Deep Learning
Category: AI Technologies
Category: AI
Category: Python with AI
Category: TensorFlow
Category: Machine Learning

What you'll learn

  • Master linear and logistic regression techniques

  • Apply Decision Trees, Random Forest, and Naive Bayes models

  • Use K-Means Clustering for data segmentation

  • Solve real-world problems with machine learning methods

Skills you'll gain

Category: Logistic Regression
Category: Random Forest Algorithm
Category: K Means Clustering Algorithm
Category: Linear Regression
Category: Linear vs Logistic Regression
Category: Decision Tree in ML
Category: Regression Analysis
Category: Classification of ML

What you'll learn

  • Master TensorFlow and Keras for model building and object detection

  • Apply RNNs and LSTM networks for sequential data tasks

  • Explore feedforward, convolutional, and recurrent neural networks

  • Build and deploy AI models to solve real-world challenges

Skills you'll gain

Category: RNNs
Category: Neural Network for AI
Category: Keras
Category: Tensorflow
Category: Tensorflow Architechture
Category: LSTM
Category: Long Short-Term Memory (ISTM)
Category: TensorFlow
Category: Deep Learning Frameworks
Category: Recurrent Neural Networks

Instructor

Simplilearn Instructor
Simplilearn
29 Courses8,351 learners

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