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via Udemy |
Go to Course: https://www.udemy.com/course/pythonai/
Certainly! Here's a detailed review and recommendation for the Coursera course based on the provided information: --- **Course Review and Recommendation: Building a Stock Price Prediction and Visualization AI from Scratch** If you are interested in gaining practical skills in data science, deep learning, and AI programming, this course on Coursera offers a straightforward and hands-on approach tailored for beginners. The course focuses on creating a simple yet effective stock price prediction and visualization AI using Python, Numpy, Matplotlib, and Pytorch. ### What You'll Learn The course is designed around three main goals: 1. **Foundations of Data Science Tools**: Master key libraries such as Numpy, Pandas, and Matplotlib. This provides a strong foundation in handling data, visualization, and basic data analysis, which are essential for any data-related work. 2. **Basics of Deep Learning**: Get comfortable with Pytorch, a popular deep learning framework. This helps you understand the basics of neural networks and deep learning models. 3. **Integrated AI Programming**: Combine your knowledge of Numpy, Pandas, Matplotlib, and Pytorch to understand the overall architecture of AI programming. You'll learn how these tools work together to build AI applications. ### Course Structure & Approach This course is ideal for Python beginners, emphasizing implementation over theoretical details. The instructor aims to have students execute various parts of the project to understand the overarching workflow. The core project involves creating a simple LSTM model to predict stock prices, but in doing so, detailed theoretical explanations of the LSTM model are deliberately omitted to keep the focus on practical skills. ### Suitability & Prerequisites The course assumes basic knowledge of Python syntax, making it accessible for those new to programming but willing to learn through hands-on projects. Since the course emphasizes implementing code rather than delving into complex theory, it's perfect for beginners who want to see tangible results quickly. ### Pros - Practical, hands-on approach suitable for newcomers - Focuses on essential libraries used in data science and AI - Clear progression from data handling to deep learning - Real-world project: stock price prediction visualization ### Cons - Limited theoretical explanations of the underlying models - Might require supplementary learning for deep understanding of LSTM or funding more advanced content later ### Final Recommendation If you're a beginner eager to get your hands dirty with data science and deep learning concepts while creating a useful application, this course is highly recommended. It's a great stepping stone into AI programming, providing foundational skills that you can build upon with more advanced courses later. --- Feel free to ask if you'd like a brief overview of specific lessons, tips on getting started, or additional resources!
本講座にて、ゼロから作成するのは、非常にシンプルな、株価予想可視化AIになります。使用するライブラリは、Numpy、Matplotlib、Pytorchです。本講座のゴールをお伝えします。一つ目のゴールは、Numpy、Pandas、Matplotlibをコントロールできるようになることで、データサイエンスの基礎を理解することです。二つ目のゴールは、Pytorchをコントロールできるようになることで、ディープラーニングの基礎を理解することです。三つ目のゴールは、Numpy、Pandas、Matplotlib、Pytorchを連携してコントロールできるようになることで、AIプログラミングの仕組みと全体像を理解することです。本講座の前提知識は、Pythonの基礎文法です。本講座の注意事項をお伝えします。本講座では、Python初心者の方に、まずは一通りのことを実装し、全体像を理解してもらうことをゴールとしています。ですので、本講座で作成するLSTMモデルの理論の詳細については、解説しませんので、ご了承ください。