Why Devs Should Prioritize Machine Learning & System Design

The tech industry has seen its share of transformative paradigm shifts, ones that often completely reinvent or revolutionize software development processes. 

One such shift occurred with the advent of cloud computing. When Amazon introduced AWS (Amazon Web Services) in 2006. This service provided businesses with a groundbreaking alternative to traditional data storage. Instead of being bound by the constraints of local servers or physical data centers, companies could now leverage Amazon's expansive and virtually limitless cloud infrastructure. 

Soon, other tech giants followed suit, realizing the potential and demand for such services. Google introduced Google Cloud, and Microsoft joined the fray with Microsoft Azure, each bringing their own unique offerings to the expanding field of cloud computing.

The influence of cloud computing has been disruptive in the truest sense of the word. According to industry experts, the introduction of cloud computing has compelled even legacy players, those rooted in traditional business models, to revise their strategies.

These businesses quickly learned that they needed to be fast, flexible, and more importantly, scalable — and they learned that this could be done by cutting their reliance on physical infrastructure and opting for a more virtual and distributed approach.

Some benefits that cloud computing offers are:

• Cloud computing offers scalable solutions by allowing businesses to scale their computing resources based on demand. 

• Cloud computing made it easier for businesses and individuals to access computing resources and services remotely over the internet.

• It offers reliable backup and storage support in case of disaster or system failures. 

• Cloud computing democratized access to advanced technologies, such as artificial intelligence, machine learning, and big data analytics, making them more accessible to businesses of all sizes.

Speaking of disruptions in the tech industry, it's impossible to overlook  AI (Artificial Intelligence), which is currently at the forefront of technological innovation. The incorporation of AI in the tech industry is a game changer for everyone. AI has helped businesses innovate in the best ways possible, like automation, improved decision-making, personalization, and much more. That ensures one thing — change is here to stay. 

Staying relevant necessitates an ongoing commitment to skill development and tool mastery. Failing to improve your skills and stay abreast of the latest trends could lead to falling behind. Competing in today's marketplace requires being armed with certain essential capabilities. Among them, machine learning and system design stand out as key necessities. 

Let's delve into a brief overview of these areas.

What is Machine Learning?#

Machine learning allows computers to learn and make decisions without being explicitly programmed. It involves creating algorithms and models to analyze and interpret large amounts of data to identify patterns and make predictions or decisions based on those patterns. It's like teaching a computer to recognize and understand things by showing examples and letting it learn from them.

Machine learning is used in various applications, such as image and speech recognition, recommendation systems, and predicting future outcomes. That is why Machine Learning (ML) is growing rapidly.

Why Learn Machine Learning?#

With the rise of big data in the early 2000s, machine learning became popular when businesses like YouTube and Facebook started storing and analyzing vast amounts of data. According to Million Insights, a market research company, the machine learning industry is projected to grow over $96 billion by 2025 (U.S. dollars).

As software developers, we must stay relevant in the field and learn the emerging technologies in the industry. Machine learning is not just a new trend. It has become necessary for developers because big companies like Meta, Google, and Uber are making machine learning an integral part of their operations. The necessity has become more apparent when we see machine learning integrated with artificial intelligence tools such as ChatGPT.

How to Learn Machine Learning?#

Whether you're an experienced software engineer managing developers or just starting your tech career, learning machine learning is essential. 

Here are a few steps you can take to learn about ML and AI the efficient way.

• First, you need to understand the fundamentals of Machine Learning, which also demands strong (not exceptional) math skills.

• The next thing is to start digging deeper into essential topics such as real datasets, neural networks, supervised and unsupervised learning, deep learning, etc.

• As it is an evolving field, get your hands on some practical machine learning courses to enhance your knowledge in the respective field. Play and learn using different ML tools to polish your skills.

• Start applying for jobs or internships. Cloud-focused interviews are new but still becoming more popular in big tech companies. Interview candidates must be aware and ready for this coming change in the recruiting procedure.

Although some fear of change is reasonable, let's remember how fascinating machine learning and artificial intelligence are. Future trends in AI are already becoming apparent in fields like content marketing and picture production, and with enough funding, the future is bright. The remarkable algorithms that power GPT-3, DALL-E, and Jasper are just a preview of what these technologies have in store.

What is System Design?#

System design is the process of creating a plan or blueprint for building a complex system. It includes identifying the components or elements of the system and defining how they will work together to achieve specific goals or solve a problem.

In simple words, system design is like designing the architecture or structure of a system, such as a software application or a physical infrastructure. It includes determining the different parts of the system, their functions, and how they will interact. The system design also considers factors like performance, scalability, reliability, and security to ensure the system functions effectively and meets the desired requirements.

Why Learn System Design?#

If you're a developer, you must have either built a distributed system or worked on applications that rely on or interact with distributed systems. And to create distributed systems, learning system design is an integral part.

• Problem-Solving and Analytical Thinking: System design teaches you to break down complex problems into smaller, more manageable parts and help analyze their interactions.

• Collaboration and Communication: System design sometimes requires collaboration with other team members, stakeholders, and experts from different domains. This will help you improve your communication and collaboration skills.

• Cost Optimization: System design evaluates trade-offs between different design choices, including costs. By understanding system design principles, you can make calculated decisions that balance functionality, performance, and cost considerations.

• Integration and Interoperability: System design involves considering how different components and systems can integrate and work together. It helps you understand how to design interfaces, define protocols, and ensure interoperability between various system parts.

How to Learn System Design?#

If you're a developer planning to start learning system design, here are three tips to help you learn system design effectively (take notes from the experts!).

• It's never too early to start learning about system design. Start taking machine learning system design courses and add another useful skill to your life. If you're a mid-level developer, learn system design immediately so you can apply for senior positions down the road.

• Next, study the "building blocks" of system design. These will help you understand how modern systems are distributed into components to help you create solutions for any problem.

• After finishing the components, learn System Design patterns and best practices. Learning patterns will help you effectively prepare for  future jobs and interviews. Moreover, it will help you with analytical thinking so you can solve problems efficiently.

Let's Stay Relevant!#

To continue a successful career as a developer, staying up-to-date with trends and learning is an integral part of your life. Educative is the best place to learn and upscale your skills. We offer fantastic learning opportunities for developers.

We suggest the Fundamentals of Machine Learning for Software Engineers course to learn more about Machine Learning. You'll be able to learn some core concepts of machine learning, like neural networks, deep learning, and supervised learning.

Check out Grokking Modern System Design Interview for Engineers & Managers to improve your system design interview skills. You'll learn about large-scale systems like Youtube, Twitter, and Instagram and get their insights into the fundamental building blocks of modern System Design.

Happy Learning!