Hybrid Python3|Swift4 Applications

🎉 **[Data Science for Swift/Python Hackers](https://www.example.com/course-page)** 🐍🇬🇧✨—

### **Course Headline:**
**BI-RADS Data Science for Swift/Python Hackers** – A course tailored for iOS and Python Developers by an expert iOS Developer.

—

### **Course Description:**

Dive into the world of **Data Science** with a twist! This course is designed specifically for Swift and Python developers who are looking to expand their skill set beyond the basics of machine learning with CoreML. **BI-RADS Data Science for Swift/Python Hackers** is your gateway to implementing sophisticated data science algorithms using iPython within Jupyter Notebooks. As a Swift programmer, you’ll find the transition to Python for data science tasks surprisingly intuitive, thanks to the clear and concise syntax of iPython.

**What You’ll Learn:**
– **Section 1: Introduction to Data Science with Python** – We kick off the course by getting you comfortable with iPython, setting up your Jupyter environment, and understanding the essentials of data manipulation and visualization in Python.

– **Section 2: Supervised Learning Mastery** – Here, we cover all you need to know about supervised learning. You’ll learn how to apply these concepts with real-world examples that will solidify your understanding.

– **Section 3: Building a Logistic Regression App in Swift** – With your Python skills sharpened, it’s time to bring the logic back to the Apple ecosystem. You’ll learn how to create a Logistic Regression Binary Based application using xCode and Swift, leveraging TensorFlow for its powerful algorithms.

– **Section 4: Final Project – The BIRADS Application** – Your culminating project involves creating an intelligent Breast Imaging-Reporting and Data System (BIRADS) that takes input features and outputs a BI-RADS Category, using the neural network you’ve developed. This application will use real data, including:
– Sample code number ID number
– Clump Thickness (1 – 10)
– Uniformity of Cell Size (1 – 10)
– Uniformity of Cell Shape (1 – 10)
– Marginal Adhesion (1 – 10)
– Single Epithelial Cell Size (1 – 10)
– Bare Nuclei (1 – 10)
– Bland Chromatin (1 – 10)
– Normal Nucleoli (1 – 10)
– Mitoses (1 – 10)
– Class: (1 for benign, 0 for malignant)

—

### **Why Take This Course?**
– **Tailored for Developers:** Designed specifically for those with a background in Swift and Python.
– **Practical Application:** Transition your knowledge from theoretical to practical with real-world applications.
– **Full Source Code Included:** You’ll receive the complete source code for the course projects, allowing you to study, debug, and learn how each piece fits together.

—

### **Who This Course Is For:**
– iOS Developers who want to explore Data Science with Python.
– Python developers looking to integrate data science into their Swift applications.
– Any developer interested in the intersection of data science, machine learning, and mobile app development.

—

### **Key Takeaways:**
– A solid understanding of iPython for data science tasks.
– Practical experience with supervised learning techniques.
– The ability to create a full-fledged data science application using Swift and TensorFlow.
– A completed BIRADS project that demonstrates your newfound data science skills in a real-world context.

—

Join us on this exciting journey into the realm of Data Science for Swift and Python developers. Enroll now and transform the way you think about mobile app development with the power of data science! 🚀

[Enroll Now](https://www.example.com/course-enrollment)!