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How to Get Started in AI and Machine Learning AI and machine learning aren’t just passing trends in an ever-evolving digital landscape – they are critical aspects of the future of our planet. Rapid development in AI has already transformed many industries, and it will continue to do so, with Forbes projecting that AI will be very big. This technology is here now, and a lot of people want to get involved. What may surprise you is that it’s possible to get a job in AI or machine learning without a specialized degree. 5 Core Skills for Getting a Job in AI and Machine Learning The idea of an AI career may sound uber-cool in a slick, futuristic kind of way, but behind the scenes, AI and machine learning jobs entail tasks and abilities that may not have everyone leaping out of bed on a Monday morning. To truly succeed in an AI career, you must have some core skills. Moreover, you should have a genuine passion for the work that is involved. Consider the following: Probability and Statistics: To say you should have a head for numbers is an understatement. Ideally, you should be excited to read about statistical theories and get giddy on probability problems. Applied Math: It’s mostly about high-level mathematics. When you’re learning about complex things like algorithms and gradient descent, you should only yawn because it’s too easy. Programming Proficiency: Python is the best language to learn when you want to start a career in machine learning or AI. Build your skills in languages like C++ and Java too. Distributed Computing: AI runs on data, and often that data is spread over many machines. Learn to handle massive datasets efficiently across distributed systems. Unix: Most AI work happens on Linux systems. Get familiar with Unix commands and tools if you’re not already. What to do Before You Apply for an AI Job As mentioned, a degree is not essential for an AI career. Of course, it would certainly boost your chances, especially as competition for artificial intelligence jobs increases in the years ahead. 1. Online Study If you’re truly motivated to get an AI career, you can undertake self-directed study. There is a plethora of fantastic options online now. Here are a few gems: Learn with Google AI: Free and beginner-friendly intro to machine learning and AI. Machine Learning by Stanford University: A Coursera course by Andrew Ng. Comprehensive and respected. Fundamentals of Deep Learning for Computer Vision by Nvidia: Learn how to build visual recognition systems. 2. Personal Projects To gain experience without a formal job, contribute on platforms like GitHub. Employers value real projects more than certificates. Tips for your GitHub project: Pick a project aligned with your current skills. Keep it under a month to finish. Ensure clean, commented, modular code. Include a README.md with dependencies, tech stack, and resources used. How to Find a Job in AI or Machine Learning You get the chance to work alongside experienced engineers, data scientists, and programmers, gaining valuable experience on smaller projects before securing a long-term role. 1. Build Your Network LinkedIn: Connect with peers, industry experts, and potential employers. AI Communities: Get active on GitHub, Kaggle, etc., to network and find jobs. Events: Attend AI meetups and tech conferences, especially in major cities. 2. Create a Shortlist As you explore the field, compile a list of 20–25 companies you’d love to work for. Research their websites and socials to see if their mission aligns with yours. 3. Judge Yourself Study job descriptions to learn the required skills and tools. Compare your abilities with what the roles demand. Close the gap through learning and practicing. 4. Continued AI Career Development Portfolio Website: Display your projects, resume, and skills. Blog: Write about AI/ML topics and share your learning process. Freelancing: Gain real-world experience through platforms like Upwork and Freelancer.

AI in Digital Marketing – The Ultimate Guide AI has evolved from a fantastical notion to a game-changer for digital marketers today. It’s become the secret engine driving personalized ads, predictive analytics, customer experiences, and much more. What is AI in Digital Marketing? AI in digital marketing uses artificial intelligence capabilities such as data collection, natural language processing, machine learning, and data analysis to get customer insights and automate marketing tasks and decisions. The advantage of AI is that it will help you gain insights into customer behaviors at speed by harvesting vast amounts of data. These can be used to respond to and tailor a customer’s needs depending on their actions and preferences. AI is also able to adapt and improve over time using feedback and new data. Artificial intelligence offers great opportunities for marketers to be more effective and personalized. This means customers get relevant content that can be triggered by actions on a site, an ad, or a branded message. But AI doesn’t replace the roles and efforts of humans! It is a technology that complements and enhances those but it requires human skills to use it effectively. AI Digital Marketing Tools While ChatGPT may be the most talked-about generative AI tool, there are so many more out there that are helping marketers in their daily roles. They can help marketers in a variety of functions from content generation to automation to SEO and design. Here are some of the most effective AI tools out there: Jasper – A content generation and optimization tool designed for augmenting content production Writer – A highly-rated content generation tool that can repurpose content and includes an AI writing assistant Optimove – A customer data platform with AI-based marketing functions Zapier – Helps automate workflows by connecting apps and services that your company uses Surfer SEO – A cloud-based on-page optimization tool that analyzes and compares your pages against what currently ranks on the SERPs Examples of AI in Digital Marketing The power of AI means it can be leveraged across many digital channels. Companies use it for social media campaigns, to automate tasks and processes, and for digital advertising. It can also be used in any industry. Beauty brands use it to deliver a tailored customer experience such as Sephora’s AI chatbot-powered shopping service, while publishers like The Economist use AI-driven programmatic advertising to target and influence ‘reluctant readers’. How to Use AI in Digital Marketing As AI technologies have become more accessible and easier to use, companies have started to use them in daily tasks such as creating content for PPC ads or setting up triggered email workflows. When we asked our membership community at the Digital Marketing Institute about AI, over half felt their roles are changing due to the technology while 44% already use it. Of those who use artificial intelligence, 45% believe it has helped increase their productivity. Content and image creation Marketing teams are often under pressure to create content quickly for many purposes and channels. However, creating good content takes time and effort, and a lot of marketers are time- and resource-poor. AI software such as ChatGPT and Jasper has exploded because it helps people generate content: that’s why they’re called generative AI tools! This could be email subject lines, ad copy, landing pages, blogs, or anything else you need for your content marketing. You can also use AI writing prompts to create catchy headlines and customize content for your audience which drives personalization. Using these tools saves time and money. However, make sure to read over any content before publishing it live to ensure it has personality and fits in with your brand voice. Customer service and support AI-driven chatbots have been around for a while as a way to communicate with and provide information to customers. When people want to get instant answers to simple queries or interact with a brand, they first go to a chatbot. However, AI has a bigger role when it comes to customers. It can improve customer experience by personalizing content and messaging, anticipating customer needs, streamlining purchasing, and directing queries or concerns to the right department or agent. Customer segmentation Customer segmentation and targeting help you identify and influence your most valuable customers. However, doing this manually can be time-consuming and costly. AI can use algorithms to segment your prospects and customers into groups or segments of people with similar interests, needs, or behaviors. You can then communicate with and target these segments with relevant and customized messaging that can be adapted and adjusted in real-time. Recommendation systems can suggest products, services, or offers that match customer preferences while Natural Language Processing (NLP) can analyze customer feedback and reviews to improve your products, services, or customer experience. Pay-per-click advertising Pay-per-click (PPC) advertising is a form of advertising where you pay when someone clicks your ad. As a strategy, PPC marketing is important as it can attract new customers through targeted campaigns, get quick results, and be easily tweaked and optimized. The Pros of AI in Digital Marketing Boosts productivity – Automate a variety of jobs so your time and effort can be redirected to more difficult and strategic tasks. Drives efficiency – Handles mundane and repetitious activities such as data input, separating marketing campaign leads, and replying to consumer queries. Reveals insights – Eliminate guesswork and provide data-driven capabilities to develop a more effective marketing approach and open up new marketing opportunities. Increases ROI – Predict buying behavior and choices by evaluating data, improving the UX, and providing consumers with the content they require to complete their buyer journey. Create and optimize content – Automate content creation to produce quality content at scale for all online channels. Personalize at scale – Analyze customer data and generate personalized recommendations or content to enhance customer experience. Predictive analysis – Forecast consumer behavior or market trends based on historical data to help more accurate and effective planning. Automate tasks – Handle routine tasks such as data analysis, customer