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Data Science at DeepLearning.AI

Explore 34 online data science courses and learning programs from DeepLearning.AI.

Overview Coursera

Overview

DeepLearning.AI is based in Palo Alto, California in the United States.

There are 34 learning opportunities created by DeepLearning.AI to develop your skills and build your data career. Click a course or program below for more information.

Courses & Programs (34)

Coursera (34)

Advanced Learning Algorithms

30 hours

Beginner

AI For Everyone

12 hours

Beginner

722,065

AI for Medical Diagnosis

20 hours

Intermediate

47,306

AI for Medical Prognosis

31 hours

Intermediate

18,515

AI For Medical Treatment

23 hours

Intermediate

16,237

Analyze Datasets and Train ML Models using AutoML

19 hours

Advanced

15,075

Building Systems with the ChatGPT API

1 hours

Beginner

Build, Train, and Deploy ML Pipelines using BERT

14 hours

Advanced

6,743

Calculus for Machine Learning and Data Science

25 hours

Beginner

2,707

Convolutional Neural Networks

39 hours

Intermediate

387,394

Convolutional Neural Networks in TensorFlow

27 hours

Intermediate

101,313

Custom and Distributed Training with TensorFlow

29 hours

Intermediate

9,728

Custom Models, Layers, and Loss Functions with TensorFlow

37 hours

Intermediate

15,234

Data Pipelines with TensorFlow Data Services

16 hours

Intermediate

15,294

Deploying Machine Learning Models in Production

33 hours

Advanced

7,901

Generative AI for Everyone

6 hours

Beginner

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

26 hours

Intermediate

430,353

Introduction to Machine Learning in Production

10 hours

Advanced

39,838

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

31 hours

Intermediate

271,578

Linear Algebra for Machine Learning and Data Science

21 hours

Beginner

11,919

Machine Learning Data Lifecycle in Production

22 hours

Advanced

15,559

Machine Learning Modeling Pipelines in Production

26 hours

Advanced

8,564

Natural Language Processing with Attention Models

37 hours

Intermediate

33,936

Natural Language Processing with Classification and Vector Spaces

35 hours

Intermediate

92,447

Natural Language Processing with Probabilistic Models

32 hours

Intermediate

39,891

Natural Language Processing with Sequence Models

25 hours

Intermediate

34,689

Neural Networks and Deep Learning

27 hours

Intermediate

1,019,001

Optimize ML Models and Deploy Human-in-the-Loop Pipelines

14 hours

Advanced

3,753

Probability & Statistics for Machine Learning & Data Science

Beginner

Sequence Models

41 hours

Intermediate

316,041

Sequences, Time Series and Prediction

14 hours

Intermediate

87,268

Structuring Machine Learning Projects

9 hours

Beginner

356,117

Supervised Machine Learning: Regression and Classification

33 hours

Beginner

Unsupervised Learning, Recommenders, Reinforcement Learning

30 hours

Beginner

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Stanford University Coursera Andrew Ng Laurence Moroney Luis Serrano Robert Crowe Cristian Bartolomé Arámburu Robert Crowe

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