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IT and Software Personal Development

Learn AI with Python

Overview: Welcome to "Learn AI with Python"! This course is your gateway to mastering Artificial Intelligence (AI) concepts and techniques using the ...

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59 Lesson

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6hr 24min

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4 students enrolled

Overview:

Welcome to "Learn AI with Python"! This course is your gateway to mastering Artificial Intelligence (AI) concepts and techniques using the Python programming language. With AI revolutionizing industries worldwide, this course empowers you to harness the power of Python to build intelligent systems and algorithms. From machine learning to deep learning and natural language processing, you'll explore a wide range of AI applications, equipping you with the skills to tackle real-world challenges and drive innovation.
  • Interactive video lectures by industry experts
  • Instant e-certificate
  • Fully online, interactive course with Professional voice-over
  • Developed by qualified first aid professionals
  • Self-paced learning and laptop, tablet, smartphone friendly
  • 24/7 Learning Assistance
  • Discounts on bulk purchases

Main Course Features:

  • Comprehensive coverage of AI fundamentals, algorithms, and libraries in Python
  • Hands-on projects and coding exercises to reinforce learning
  • Exploration of machine learning techniques, including supervised and unsupervised learning
  • Implementation of neural networks and deep learning models with TensorFlow and Keras
  • Introduction to natural language processing (NLP) for text analysis and sentiment analysis
  • Guidance on deploying AI models and integrating them into applications
  • Real-world case studies and examples to illustrate AI concepts in practice
  • Access to a supportive online community for collaboration and assistance

Who Should Take This Course:

  • Aspiring data scientists and AI enthusiasts looking to kickstart their career in AI
  • Python developers interested in expanding their skill set to include AI and machine learning
  • Students and professionals seeking to leverage AI for solving real-world problems

Learning Outcomes:

  • Master AI concepts and techniques using Python programming
  • Develop machine learning models for classification, regression, and clustering tasks
  • Build and train neural networks and deep learning models for various applications
  • Perform text analysis and sentiment analysis using natural language processing (NLP)
  • Deploy AI models and integrate them into web applications or other systems
  • Enhance problem-solving skills by applying AI algorithms to real-world datasets
  • Debug and optimize AI models for improved performance and accuracy
  • Stay updated with the latest advancements and trends in AI and machine learning.

Certification

Once you’ve successfully completed your course, you will immediately be sent a digital certificate. All of our courses are fully accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Our certifications have no expiry dates, although we do recommend that you renew them every 12 months.

Assessment

At the end of the Course, there will be an online assessment, which you will need to pass to complete the course. Answers are marked instantly and automatically, allowing you to know straight away whether you have passed. If you haven’t, there’s no limit on the number of times you can take the final exam. All this is included in the one-time fee you paid for the course itself.
Course Content
59 Lectures 6hr 24min
  • ImgIntroduction to Predictive Analysis

  • ImgRandom Forest and Extremely Random Forest

  • ImgDealing with Class Imbalance

  • ImgGrid Search

  • ImgAdaboost Regressor

  • ImgPredicting Traffic Using Extremely Random Forest Regressor

  • ImgTraffic Prediction

  • ImgDetecting patterns with Unsupervised Learning

  • ImgClustering

  • ImgClustering Meanshift

  • ImgClustering Meanshift Continues

  • ImgAffinity Propagation Model

  • ImgAffinity Propagation Model Continues

  • ImgClustering Quality

  • ImgProgram of Clustering Quality

  • ImgGaussian Mixture Model

  • ImgProgram of Gaussian Mixture Model

  • ImgClassification in Artificial Intelligence

  • ImgProcessing Data

  • ImgLogistic Regression Classifier

  • ImgLogistic Regression Classifier Example Using Python

  • ImgNaive Bayes Classifier and its Examples

  • ImgConfusion Matrix

  • ImgExample os Confusion Matrix

  • ImgSupport Vector Machines Classifier(SVM)

  • ImgSVM Classifier Examples

  • ImgConcept of Logic Programming

  • ImgMatching the Mathematical Expression

  • ImgParsing Family Tree and its Example

  • ImgAnalyzing Geography Logic Programming

  • ImgPuzzle Solver and its Example

  • ImgWhat is Heuristic Search

  • ImgLocal Search Technique

  • ImgConstraint Satisfaction Problem

  • ImgRegion Coloring Problem

  • ImgBuilding Maze

  • ImgPuzzle Solver

  • ImgNatural Language Processing

  • ImgExamine Text Using NLTK

  • ImgRaw Text Accessing (Tokenization)

  • ImgNLP Pipeline and Its Example

  • ImgRegular Expression with NLTK

  • ImgStemming

  • ImgLemmatization

  • ImgSegmentation

  • ImgSegmentation Example

  • ImgSegmentation Example Continues

  • ImgInformation Extraction

  • ImgTag Patterns

  • ImgChunking

  • ImgRepresentation of Chunks

  • ImgChinking

  • ImgChunking wirh Regular Expression

  • ImgNamed Entity Recognition

  • ImgTrees

  • ImgContext Free Grammar

  • ImgRecursive Descent Parsing

  • ImgRecursive Descent Parsing Continues

  • ImgShift Reduce Parsing