Your Guide to Learning Swift for Data Science from Scratch
he Swift programming language is quickly becoming the language of choice for a lot of data science experts and professionals. Swift’s flexibility, ease of use, excellent documentation, and quick execution speed are key reasons behind the language’s recent prominence in the data science space.
Swift is a more efficient, stable and secure programming language as compared to Python. In fact, Swift is also a good language to build for mobile. In fact, it’s the official language for developing iOS applications for the iPhone!
The cherry on the cake for Swift? It has the support of the likes of Google, Apple, and FastAI behind it!
“I always hope that when I start looking at a new language, there will be some mind-opening new ideas to find, and Swift definitely doesn’t disappoint. Swift tries to be expressive, flexible, concise, safe, easy to use, and fast. Most languages compromise significantly in at least one of these areas.” – Jeremy Howard
And when Jeremy Howard endorses a language and starts using it for his daily data science work, you need to drop everything and listen.
In this free course on Swift for Data Science, we will learn about Swift as a programming language and how it fits into the data science space. If you’re a Python user, you’ll notice the subtle differences and the incredible similarities between the two. We showcase Swift code as well in the course so get started!
Why Swift for Data Science?
It’s a fair question. Most data science folks you’ll talk to will encourage you to learn Python before Swift. But as we covered above, Swift has its own share of advantages over Python as the programming language you should learn for data science.
Here’s Jeremy Howard espousing the value and awesomeness of the Swift programming language:
Key Questions To Answer for Swift Programming Beginners:
- What is Swift?
- Are Swift and Python similar?
- If not, then how is Swift programming different from Python?
- Why is Swift required to perform data science tasks?
- What are some industrial use cases of Swift for Data Science?
- Can we use Swift for deep learning as well?
- What are some unique features of Swift?
- What are some key challenges of Swift for Data Science?
- How is Swift being used in the industry?
Who is the Swift for Data Science Course for?
The Swift for Data Science course is targeted towards anyone who:
- Wants to learn data science using a new but upcoming programming language
- Wants to learn the Swift programming language
- Is interested in exploring the world of data science
- Is curious to explore a new programming language beyond Python!
What do you need to get started with the Swift for Data Science course?
Here’s what you’ll need:
- A working laptop/desktop with 4 GB RAM
- A working Internet connection
- Basic knowledge of core machine learning algorithms
- Optional - Knowledge of Python programming will help you appreciate the differences between that and Swift plus help you make the transition easier
You’re ready to take your first steps into the world of Swift programming for Data Science!
Common Questions Beginners Ask About Swift
We saw these questions earlier. Let’s quickly go through them one by one.
What is Swift?
Swift is an open-source programming language announced in 2014. Though it is a general-purpose language, it is fast gaining ground in the Data Science space.
Are Swift and Python similar?
Though Swift and Python are different languages, they are similar in many ways. Both are open-source, though the Swift stack also has a different version for macOS users. Both swift and Python include some functional programming tools and a lot of the data structures in both Python and Swift are similar - like lists, tuples, dictionaries, etc.
How is Swift different from Python?
The syntax of Swift is slightly different from that of Python. Just like Python, Swift was essentially developed by Apple as a holistic mobile application programming language, but its uses in Data Science and Machine Learning catapulted it to fame. The other differences are:
- Swift is much faster than Python
- Swift catches your error before runtime, unlike Python - where you catch your mistakes after the code has run
- Python is essentially a wrapper on C, unlike Swift which is its own standalone language
Why do I need to learn about Swift?
In the fast-evolving field of Data Science, it is important to stay updated on recent developments. Just like Python replaced R, there has been a slew of new programming languages geared towards speed and performance - Swift leads the pack here. Though much newer, it is now in the top 10 languages used by developers and the industry’s support for it only enhances the need for learning Swift.
How can I use Swift for Data Science Purposes?
You need no better endorsement of technology than Google. One of the most popular machine learning frameworks, Tensorflow introduced a Swift for TensorFlow in 2018. This now combined with other Open Source libraries like SwiftAI, SwiftPlot, etc builds a powerful arsenal of tools for Data Science. Not only this, but for MacUsers, it is compatible with the CoreML library - you can now use it in Google Colab
Can Swift be used for Deep Learning too?
In short, yes! Swift for Tensorflow(S4TF) library supports deep learning architectures in Swift. Along with CoreML, Swift also has pre-trained models for ComputerVision like ImageNet and ResNet, and GPT-2, BERT, etc for NLP
What are some other unique features of Swift?
What if you could develop a mobile application which automatically tells you if it is a dog or a cat that you are looking at? Since Swift can be combined with CoreML, it can also be used for data science functionalities in mobile applications. Some other unique features are:
- It is compatible with Python and C.This means that Python libraries like Numpy, Scikit-learn etc. can be easily used just by importing them in Swift
- Other Python APIs can also be used with just importing Python
- Apart from macOS, Swift can also be used in watchOS, tvOS, etc. So it can easily be the next big thing in IoT
What are the main disadvantages of Swift?
There are some disadvantages of Swift as well.
- The language is very new compared to a veteran language like Python - so it is still under continuous development
- Since newer versions of Swift keep coming up, it tends to make development in Swift unstable
How is Swift being used in the industry?
Swift is being used by top companies both as a general-purpose programming language and for Data Science as well. Companies using Swift include Uber, Slack, Lyft, LinkedIn, etc. Stay ahead of the curve before the migration from Python happens by enrolling in this free tutorial!
Course curriculum
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1
Introduction
- Getting Started
- Why Swift?
- AI&ML Blackbelt Plus Program (Sponsored)
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2
Swift Basics for Data Analysis
- The Swift Ecosystem
- Setting up the Environment
- Basics of Swift programming - I
- Basics of Swift programming - II
- Python with Swift
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3
Machine Learning with Swift and TensorFlow
- The Swift4Tensorflow Library
- About the Dataset and Setup
- Implementation of MNIST Image Classification
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4
Bonus Chapter: NLP Based iOS Apps uwing Swift
- Introduction
- Setting up the system
- Basic Text Processing
- Language Identification in iOS
- Spell Checking and Correction
- Part Of Speech (POS) Tagging
- Identifying People, Organization, etc. from the Text (Named Entity Recognition)
- Performing Sentiment Analysis on iOS
- Word Embeddings
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5
What Next?
- Next Steps
Instructor(s)
FAQ
Common questions related to the Swift for Data Science course
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Who should take the Swift for Data Science course?
We have curated the Swift for Data Science course for beginners with the Swift programming language. You should take the course if you are interested in broadening your data science skillset, learning a new programming language, and want to add a hot and upcoming tool to your budding data science resume!
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I have decent programming experience but no background in machine learning. Is this course right for me?
You would need to have an idea of the core machine learning algorithms. We will guide you on how to use Swift for data science to build machine learning algorithms so you would at least need to know what is supervised and unsupervised learning, and the difference between regression and classification problems.
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What is the fee for the course?
This course is free of cost!
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How long would I have access to the “Swift for Data Science” course?
Once you register, you will have 6 months to complete the course. If you visit the course 6 months after your initial registration, you will need to enrol in the course again. Your past progress will be lost.
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How much effort do I need to put in for this course?
You can complete the “Swift for Data Science” course in a few hours.
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I’ve completed this course and have a good grasp on the Swift programming language. What should I learn next?
The next step in your journey is to build on what you’ve learned so far. We recommend taking the popular “Applied Machine Learning” course.
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Can I download the videos in this course?
We regularly update the “Swift for Data Science” course and hence do not allow videos to be downloaded. You can visit the free course anytime to refer to these videos.