Edureka
Mastering AI: Neural Nets, Vision System, Speech Recognition 专项课程
Edureka

Mastering AI: Neural Nets, Vision System, Speech Recognition 专项课程

Advance Your AI Skills with Deep Learning, Computer Vision & Speech Recognition. In this AI specialization, dive deep into neural networks, vision systems, and enable speech recognition using real-world tools. Designed for learners ready to advance their AI careers.

Edureka

位教师:Edureka

包含在 Coursera Plus

深入学习学科知识
中级 等级

推荐体验

4 月 完成
在 5 小时 一周
灵活的计划
自行安排学习进度
深入学习学科知识
中级 等级

推荐体验

4 月 完成
在 5 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Analyze and apply fundamental Python functions and methods.

  • Utilize and apply various machine learning models effectively.

  • Design and optimize neural networks for AI applications.

  • Explain and implement image, video, and audio processing methods.

要了解的详细信息

可分享的证书

添加到您的领英档案

授课语言:英语(English)

了解顶级公司的员工如何掌握热门技能

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

精进特定领域的专业知识

  • 向大学和行业专家学习热门技能
  • 借助实践项目精通一门科目或一个工具
  • 培养对关键概念的深入理解
  • 通过 Edureka 获得职业证书

专业化 - 4门课程系列

Python and Statistics Foundations

Python and Statistics Foundations

第 1 门课程11小时

您将学到什么

  • Write Python programs using core concepts like variables, data types, and control flow.

  • Apply NumPy and Pandas to manipulate and analyze data efficiently.

  • Create insightful data visualizations using Matplotlib, Seaborn, and Plotly for effective reporting.

  • Perform statistical analysis and probability tests to solve data-driven problems and validate hypotheses.

您将获得的技能

类别:Statistical Hypothesis Testing
类别:Pandas (Python Package)
类别:Python Programming
类别:NumPy
类别:Plotly
类别:Descriptive Statistics
类别:Data Visualization Software
类别:Probability & Statistics
类别:Statistical Analysis
类别:Exploratory Data Analysis
类别:Statistics
类别:Data Visualization
类别:Matplotlib
类别:Probability Distribution
类别:Data Analysis
类别:Programming Principles
类别:Seaborn
类别:Data Science
Applied Machine Learning with Python

Applied Machine Learning with Python

第 2 门课程14小时

您将学到什么

  • Explore machine learning algorithms, including supervised, unsupervised, and semi-supervised methods.

  • Apply decision trees, random forests, and K-means clustering for classification and clustering.

  • Develop machine learning models to gain insights and make predictions from real-world data.

  • Enhance model accuracy by applying model-boosting techniques and evaluating their effectiveness.

您将获得的技能

类别:Supervised Learning
类别:Machine Learning
类别:Machine Learning Methods
类别:Data Analysis
类别:Dimensionality Reduction
类别:Statistical Machine Learning
Practical Deep Learning with Python

Practical Deep Learning with Python

第 3 门课程12小时

您将学到什么

  • Understand the core components of deep learning models and their role in AI.

  • Apply CNN, R-CNN, and Faster R-CNN for object detection tasks.

  • Implement RNNs and LSTMs for sequential data processing.

  • Optimize and evaluate deep learning models for improved performance.

您将获得的技能

类别:Python Programming
类别:Artificial Intelligence
类别:Machine Learning Methods

您将学到什么

  • Analyze speech waveforms and apply audio signal processing techniques.

  • Develop and implement computer vision algorithms using OpenCV.

  • Perform morphological operations on images and videos for data manipulation.

  • Apply speech recognition techniques for digitizing and analyzing audio signals.

您将获得的技能

类别:Computer Vision
类别:Applied Machine Learning

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

Edureka
Edureka
98 门课程102,390 名学生

提供方

Edureka

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