Master Python & Generative Ai For Advanced Analytics
Free Download Master Python & Generative Ai For Advanced Analytics
Published 10/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.33 GB | Duration: 3h 44m
Master Python and Generative AI to enhance your skills in advanced analytics
What you'll learn
Understand the core concepts and applications of Generative AI.
Master Python programming for building AI-driven analytical models.
Implement Generative Adversarial Networks (GANs) in Python.
Learn data augmentation techniques for advanced analytics.
Explore text analysis and processing with Generative AI tools.
Apply image processing techniques using Python and AI libraries.
Optimize model performance through training and troubleshooting.
Use Python libraries for data manipulation and visualization.
Develop predictive models using AI-driven insights.
Gain practical experience with real-world projects in analytics.
Requirements
Basic understanding of Python programming
Familiarity with machine learning concepts is helpful but not required
Access to a computer with Python installed
Willingness to learn
Description
Unlock the power of Python and Generative AI in advanced analytics with this comprehensive course designed for data enthusiasts, analysts, and developers. This course will equip you with the skills to harness the latest in AI technology, allowing you to build and apply generative models for tasks like data augmentation, text analysis, image processing, and predictive modeling.Starting with the foundational concepts of Generative AI, you will explore various types of generative models and understand their applications in real-world analytics. As you move through the course, you will delve into Python programming concepts essential for working with AI, covering data manipulation, visualization, and machine learning libraries.The course also includes hands-on projects such as constructing Generative Adversarial Networks (GANs) and using them for stock market trend predictions. You'll gain in-depth knowledge of data preparation, model training, optimization techniques, and troubleshooting strategies for achieving high-performance models.By the end of this course, you will be equipped with the knowledge to apply generative AI techniques in various fields, enhancing your data analysis capabilities and leveraging AI for predictive insights and improved data-driven decisions.Whether you're a beginner or an experienced programmer, this course is tailored to help you master advanced Python and generative AI for your analytics needs!
Overview
Section 1: Foundational Concepts of Generative AI
Lecture 1 Course Outline and Goal
Lecture 2 Introduction to Generative AI
Lecture 3 Applications in Advanced Analytics
Lecture 4 Different types of Generative Models
Lecture 5 Generative AI vs. Traditional ML
Lecture 6 Course Structure and Learning Objectives
Section 2: Python Programming for Generative AI
Lecture 7 Python for Generative AI Workflows
Lecture 8 Setting Up the Environment
Section 3: Core Python Programming Concepts
Lecture 9 Variables and Data types
Lecture 10 Data Structures in Python.
Lecture 11 Control flows in python
Lecture 12 Functions in Python
Lecture 13 Object Oriented Programming in Python
Lecture 14 Regular Expressions in Python
Lecture 15 Modules in Python
Lecture 16 File Handling in Python
Lecture 17 Error Handling in Python
Section 4: Essential Python Libraries for Generative AI
Lecture 18 Essential Python Libraries for Generative AI(Theory)
Lecture 19 Data manipulation
Lecture 20 Data visualization
Lecture 21 Image Processing
Lecture 22 Machine Learning tools
Lecture 23 Model Building and Training
Section 5: Model Building and Training
Lecture 24 Data Wrangling for Python (Part 1)
Lecture 25 Data Wrangling for Python (Part 2)
Lecture 26 Advanced Python Concepts
Lecture 27 Generative AI Libraries
Section 6: Building Generative Models
Lecture 28 Understanding Generative Adversarial Networks
Lecture 29 Constructing Your First GAN with Python
Lecture 30 Model Training and Optimization Techniques
Lecture 31 Troubleshooting Training Challenges
Lecture 32 Understanding Model Performance
Section 7: Generative AI Applications for Advanced Analytics
Lecture 33 Data Generation
Lecture 34 Augmentation for Improved Analysis
Lecture 35 Advanced Text Analysis with Generative AI
Lecture 36 Generative AI for Images & Signals
Lecture 37 7.5 Predictive Analytics with Generative AI
Lecture 38 Analytics Insights with Generative AI
Lecture 39 Applications of Generative AI in Advanced Analytics
Section 8: Project Title: "Generative AI-powered Stock Market Trend Prediction"
Lecture 40 8.1 Data Collection & Preprocessing
Lecture 41 8.2 Model Building
Lecture 42 8.3 Data Generation & Trend Analysis
Lecture 43 Evaluation
Section 9: Conclusion
Lecture 44 Course Recap and Key Learnings
Lecture 45 The Future of Generative AI and Impact on Advanced Analytics
Lecture 46 Additional Resources and Learning Paths
Data analysts looking to expand their AI skills,Python developers interested in advanced analytics,Machine learning enthusiasts seeking practical AI applications,Students of data science and AI,Professionals aiming to integrate AI into their workflows,Beginners with basic Python knowledge wanting to explore AI
Homepage
https://www.udemy.com/course/master-python-generative-ai-for-advanced-analytics/Rapidgator
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