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Deeplearning.AI Courses

Deeplearning.AI courses can help you learn how machine learning and artificial intelligence techniques are developed and applied across different tasks. You can build skills in neural networks, model evaluation, data preparation, and modern generative AI methods. Many courses introduce tools such as Python libraries, cloud environments, and frameworks that support experimenting with models and strengthening practical AI workflows.


Popular Deeplearning.AI Courses and Certifications


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    DeepLearning.AI

    Deep Learning

    Skills you'll gain: Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Computer Vision, Transfer Learning, Deep Learning, Image Analysis, Hugging Face, Natural Language Processing, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Applied Machine Learning, Embeddings, Supervised Learning, Keras (Neural Network Library), Machine Learning, Debugging, Performance Tuning, PyTorch (Machine Learning Library), Data Preprocessing

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
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    147K reviews

    Intermediate · Specialization · 3 - 6 Months

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    Multiple educators

    Machine Learning

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Transfer Learning, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Data Preprocessing

    4.9
    Rating, 4.9 out of 5 stars
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    38K reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: Preview
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    DeepLearning.AI

    AI For Everyone

    Skills you'll gain: AI Product Strategy, Responsible AI, Data Ethics, AI Enablement, Artificial Intelligence, Machine Learning, Data Science, Deep Learning, Artificial Neural Networks

    4.8
    Rating, 4.8 out of 5 stars
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    51K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: New
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    Status: Free Trial
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    Status: AI skills
    AI skills
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    DeepLearning.AI

    PyTorch for Deep Learning

    Skills you'll gain: PyTorch (Machine Learning Library), Model Deployment, Convolutional Neural Networks, Transfer Learning, Generative AI, Deep Learning, Image Analysis, MLOps (Machine Learning Operations), Data Pipelines, Embeddings, Artificial Neural Networks, Model Evaluation, Data Preprocessing, Software Visualization, Computer Vision, Natural Language Processing, Machine Learning

    4.8
    Rating, 4.8 out of 5 stars
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    60 reviews

    Intermediate · Professional Certificate · 1 - 3 Months

  • Status: Preview
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    DeepLearning.AI

    Generative AI with Large Language Models

    Skills you'll gain: Generative AI, Large Language Modeling, Generative Model Architectures, LLM Application, Prompt Engineering, Model Deployment, Python Programming, Applied Machine Learning, Scalability, Natural Language Processing, Responsible AI, Machine Learning, Model Evaluation, Reinforcement Learning

    4.8
    Rating, 4.8 out of 5 stars
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    3.6K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    DeepLearning.AI

    Mathematics for Machine Learning and Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Machine Learning Algorithms, Data Preprocessing, Machine Learning, Machine Learning Methods

    4.6
    Rating, 4.6 out of 5 stars
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    3.1K reviews

    Intermediate · Specialization · 1 - 3 Months

What brings you to Coursera today?

  • Status: Free Trial
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    DeepLearning.AI

    Neural Networks and Deep Learning

    Skills you'll gain: Deep Learning, Artificial Neural Networks, Convolutional Neural Networks, Applied Machine Learning, Supervised Learning, Recurrent Neural Networks (RNNs), Python Programming, Linear Algebra, Calculus

    4.9
    Rating, 4.9 out of 5 stars
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    124K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Multiple educators

    DeepLearning.AI Data Engineering

    Skills you'll gain: Apache Airflow, Data Modeling, Data Pipelines, Data Storage, Data Architecture, Requirements Analysis, Data Warehousing, Query Languages, Data Preprocessing, Apache Hadoop, Vector Databases, Data Lakes, Amazon Web Services, File Systems, Apache Spark, Database Systems, Feature Engineering, Dataflow, Data Integration, Data Management

    4.7
    Rating, 4.7 out of 5 stars
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    572 reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
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    DeepLearning.AI

    DeepLearning.AI Data Analytics

    Skills you'll gain: Data Storytelling, Web Scraping, Google Sheets, Data Visualization, Data Presentation, Spreadsheet Software, Large Language Modeling, Tableau Software, Data Literacy, Dashboard, LinkedIn, Pandas (Python Package), Time Series Analysis and Forecasting, Probability & Statistics, Extract, Transform, Load, Statistical Analysis, Statistics, Data Manipulation, Data Analysis, Descriptive Statistics

    4.8
    Rating, 4.8 out of 5 stars
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    239 reviews

    Beginner · Professional Certificate · 3 - 6 Months

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    DeepLearning.AI

    Machine Learning in Production

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Cloud Deployment, Continuous Deployment, Model Evaluation, Data Preprocessing, Machine Learning, Applied Machine Learning, Data Validation, Feature Engineering, Data Quality, Debugging, Continuous Monitoring, Data Pipelines

    4.8
    Rating, 4.8 out of 5 stars
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    3.3K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    DeepLearning.AI

    DeepLearning.AI TensorFlow Developer

    Skills you'll gain: Tensorflow, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Computer Vision, Model Evaluation, Transfer Learning, Image Analysis, Keras (Neural Network Library), Natural Language Processing, Time Series Analysis and Forecasting, Deep Learning, Embeddings, Artificial Neural Networks, Generative AI, Applied Machine Learning, Classification Algorithms, Predictive Modeling, Data Preprocessing, Forecasting, Machine Learning

    4.7
    Rating, 4.7 out of 5 stars
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    25K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Preview
    Preview
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    DeepLearning.AI

    AI Python for Beginners

    Skills you'll gain: Large Language Modeling, Prompt Engineering, Artificial Intelligence, Jupyter, Python Programming, Data Analysis, AI Enablement, Application Development, Scripting, Programming Principles, Automation, Application Programming Interface (API), Debugging, Data Structures

    4.8
    Rating, 4.8 out of 5 stars
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    218 reviews

    Beginner · Course · 1 - 4 Weeks

Searches related to deeplearning.ai

deeplearning.ai data engineering
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In summary, here are 10 of our most popular deeplearning.ai courses

  • Deep Learning: DeepLearning.AI
  • Machine Learning: DeepLearning.AI
  • AI For Everyone: DeepLearning.AI
  • PyTorch for Deep Learning: DeepLearning.AI
  • Generative AI with Large Language Models: DeepLearning.AI
  • Mathematics for Machine Learning and Data Science: DeepLearning.AI
  • Neural Networks and Deep Learning: DeepLearning.AI
  • DeepLearning.AI Data Engineering: DeepLearning.AI
  • DeepLearning.AI Data Analytics: DeepLearning.AI
  • Machine Learning in Production: DeepLearning.AI

Frequently Asked Questions about Deeplearning Ai

Deeplearning.AI is an organization founded by Andrew Ng, aimed at advancing the field of artificial intelligence (AI) through education and research. It plays a crucial role in making deep learning accessible to a broader audience, providing resources and courses that equip individuals with the skills needed to thrive in this rapidly evolving field. As AI continues to transform industries, understanding deep learning is essential for anyone looking to stay relevant in the job market.‎

With a background in deeplearning.AI, you can pursue various roles in the tech industry. Positions such as machine learning engineer, data scientist, AI researcher, and deep learning engineer are common pathways. These roles often involve developing algorithms, analyzing data, and creating AI models that can solve complex problems. The demand for professionals with deep learning expertise is growing, making it a promising career choice.‎

To succeed in Deeplearning.AI, you should focus on acquiring several key skills. Proficiency in programming languages like Python is essential, as it is widely used in AI development. Understanding mathematics, particularly linear algebra and calculus, is also important for grasping the underlying principles of deep learning. Familiarity with machine learning concepts and frameworks, such as TensorFlow or PyTorch, will further enhance your capabilities in this field.‎

Some of the best Deeplearning.AI courses online include the DeepLearning.AI TensorFlow Developer Professional Certificate and the TensorFlow 2 for Deep Learning Specialization. These programs offer comprehensive training in deep learning techniques and practical applications, helping you build a solid foundation in this area.‎

Yes. You can start learning Deeplearning.AI on Coursera for free in two ways:

  1. Preview the first module of many Deeplearning.AI courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate from Deeplearning.AI, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn from Deeplearning.AI effectively, start by identifying your current skill level and setting clear goals. Enroll in introductory courses to build foundational knowledge, then progress to more advanced topics. Engage with hands-on projects and exercises to apply what you've learned. Joining online communities and forums can also provide support and enhance your learning experience.‎

Typical topics covered in Deeplearning.AI courses include neural networks, natural language processing, computer vision, and reinforcement learning. These courses often explore the theoretical aspects of deep learning as well as practical applications, ensuring a well-rounded understanding of the field.‎

For training and upskilling employees, the DeepLearning.AI Data Engineering Professional Certificate is an excellent choice. It equips teams with the necessary skills to manage and analyze data effectively, which is essential for implementing deep learning solutions in any organization.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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