Edureka
Mastering AI: Neural Nets, Vision System, Speech Recognition Specialization
Edureka

Mastering AI: Neural Nets, Vision System, Speech Recognition Specialization

Master AI to Build Intelligent Systems and Drive Innovation

Edureka

Instructor: Edureka

Included with Coursera Plus

Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 months
at 5 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 months
at 5 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • 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.

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Taught in English
Recently updated!

February 2025

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  • Develop a deep understanding of key concepts
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Specialization - 4 course series

What you'll learn

  • 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.

Skills you'll gain

Category: Data Analysis
Category: Descriptive Statistics
Category: Data Manipulation
Category: Probability
Category: Probability & Statistics
Category: Programming Principles
Category: Plotly
Category: NumPy
Category: Statistical Hypothesis Testing
Category: Exploratory Data Analysis
Category: Seaborn
Category: Data Science
Category: Pandas (Python Package)
Category: Python (Programming Language)
Category: Matplotlib
Category: Data Visualization
Category: Statistical Analysis
Category: Statistical Methods
Category: Python Programming
Category: Statistics
Category: Data Visualization Software

What you'll learn

  • 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.

Skills you'll gain

Category: Data Analysis
Category: Data Mining
Category: Supervised Learning
Category: Regression Analysis
Category: Machine Learning Methods
Category: Linear Regression
Category: Data-Driven Decision-Making
Category: Classification And Regression Tree (CART)
Category: Machine Learning
Category: Unsupervised Learning
Category: Decision Tree Learning
Category: Analytics
Category: Association Rule Mining and Recommendation
Category: Predictive Modeling
Category: Feature Engineering
Category: Statistical Modeling
Category: Random Forest Algorithm
Category: Applied Machine Learning
Category: Statistical Analysis
Category: Machine Learning Algorithms
Category: Statistical Methods
Category: Python Programming

What you'll learn

  • 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.

Skills you'll gain

Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Analyzing different types frameworks
Category: Natural Language Processing
Category: Supervised Learning
Category: Implementing Optimizing Algorithms
Category: Creating models with different algorithms
Category: Machine Learning
Category: Network Architecture
Category: Image Analysis
Category: Manipulating complex datasets
Category: Artificial Neural Networks
Category: Deep Learning
Category: Computer Vision
Category: Applied Machine Learning
Category: Building SLP and MLP models

What you'll learn

  • 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.

Skills you'll gain

Category: Morphological Image Operations
Category: Deep Learning
Category: Speech Recognition
Category: Natural Language Processing
Category: Data Processing
Category: Image and Video Processing with OpenCV
Category: Computer Vision
Category: Applied Machine Learning
Category: Image Analysis
Category: Artificial Intelligence
Category: Python Programming
Category: Speech Analysis and Processing

Instructor

Edureka
Edureka
66 Courses70,784 learners

Offered by

Edureka

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