AI for Business
Do you want to use AI in your business but don’t know exactly how it works or where to start I’ve put together a comprehensive non-technical course along with six unique tools to help you start your AI Journey today my name is Omar I’ve been helping many organizations all over the world apply AI to solve real world problems and I’m extremely passionate about sharing this knowledge with the world AI is so powerful I’ve seen it firsthand and I want you to be able to tap into this power today you’ll
learn the fundamentals of Ai and machine learning explore more than 80 practical use cases discover how to select your first AI projects understand how to plan launch and evaluate machine learning proof of Concepts determine the ideal structure for your AI team and finally understand how to scale AI adoption across your company welcome to the AI for business course your actionable introduction to this amazing world and how to apply it in your day-to-day work the course consists of seven episodes let’s have a quick tour of what you’re
going to be learning in each first things first what is AI in the first episode you’re going to be learning about the different types and patterns of AI and what it can and cannot do we’ll start by exploring the difference between AI machine learning and deep learning we’re also going to explore the different types of machine learning supervised learning which can help you make predictions like predicting store demand or providing personalized recommendations for your customers unsupervised learning which can help you
find patterns natural groupings like unique customer segments for example or even anomalies in your data and reinforcement learning which can help you optimize planning and actions we’re also going to explore the rapidly growing space of generative Ai and large language models which leverage the latest techniques in semi-supervised learning we’ll see how deep learning is becoming really good at understanding language voice and images this advancement is enabling different applications like self-driving cars
How Businesses Are Using Artificial Intelligence In 2024 – Forbes
digital assistant like Siri and Alexa and document analysis AI thrives on data if you don’t have good data it’s going to be really hard to get value out of AI in many cases we’ll explore the different kinds of data you need both in terms quality and quantity for different types of problems we’ll also get introduced to the concept of label data which is essential for making predictions most of the time the next two episodes dive deep into to AI use cases aiming to give you a comprehensive grasp of today’s machine
learning applications we’ll be exploring more than 80 different use cases across different domains you know like supply chain Healthcare manufacturing retail e-commerce government you name it we’re also going to explore those use cases in different functions like HR Marketing sales engineering Etc the second episode is going to zoom in on non-generative AI use cases while the third one is going to be totally dedicated to this growing Fe field of generative Ai and large language models where we’re going to see
the different and interesting use cases in those domains in marketing for instance we’ll see how machine learning could be used for hyper targeting personalized recommendations cross on upselling Dynamic price optimization and more we’ll see how leading companies like Netflix Amazon and Starbucks employ these methods to reap imense Returns on their marketing investments in the realm of manufacturing and supply chain Mach learning could lead to substantial cost savings we’ll see use cases like predictive maintenance for example which
could be utilized to foresee potential failures in machines before they happen and recommend the best corrective actions we’re also going to be exploring different use cases in these two domains like production yield optimization Logistics optimization demand for casting and more other use cases will be exploring includes cyber security threat detection credit risk scoring and assessment for banking HR applications like predicting an applicant’s performance before they join traffic optimization for Smart City applications
and more we’ll be exploring these use cases and share some success stories in the real world the main tool we’ll be using for this episode is going to be ai- cases.com it’s a website that we’ve put together that offers carefully curated resources on many proven AI use cases that have been deployed in production across numerous organizations the Aris of generative AI has been both rapid and widespread touching almost every single sector our third episode is going to be entirely dedicated for this
branch of AI we’re going to explore its diverse applications from chatting with Enterprise data to building language interfaces for different systems like e-commerce and travel to generating images and videos automating code creation deploying autonomous agents and more how to choose your first AI project that’s going to be the focus of the fourth episode you learn how to brainstorm and formulate ideas for your AI initiatives you’ll then learn how to communicate these by using the AI idea canvas it’s a great tool that can help
you map out the most important elements of your AI project and collaborate with your team and then you’ll learn how to evaluate these ideas based on Technical and business criteria like the expected business Roi technical feasibility and more factors machine learning projects inherently carry some level of risk because simply you don’t know what you don’t know right you don’t know for example if your data would carry sufficient predictive power for the use case you have in mind until you start
trying things out you’re also typically uncertain about the resulting business impact the stakeholder adoption the technical complexity and other variables until you start actually embarking on the project a proof of concept can help you mitigate these risks by testing a smaller version of your idea in a short time frame backed by clear evaluation criteria this approach allows you to discover and address potential challenges early on in your journey before investing too much time energy.
This episode we’re going to dive deeper into how to design these proof of Concepts how to launch them how to manage them and more importantly how to use them when planning to scale them to production a bonus for this episode is going to be the AI PC template which highlights the 10 most fundamental elements you would generally consider when planning your proof of Concepts you also get access to many AI proof of concept examples for different use cases should you be building an in-house AI team or Outsource each has their own
strengths depending on so many factors like time to Market whether AI score competency to your business the IP ownership the availability of skills and so forth in the sixth episode we’re going to expand on this comparison and then we’re going to dive deeper into the structure of an AI team there are so many different structures for an AI team that you can have we’re going to explore the core roles like data scientists data Engineers machine learning Ops engineers and software Engineers optional roles like research
engineers and AI product managers Etc and support roles we’re going to explore eight different scenarios whether you are a startup an established business an AI first company or not we’re going to explore these different scenarios see different theme structures and the bonus of that episode is going to be the a I rolls map which highlights those different rols and provides these different scenario examples after learning all these Concepts it’s time to start your journey that’s going to be the focus of the seventh and last
episode of this course we’re going to explore the three major phases that most companies go through when adopting AI starting from the early exploration and prototyping moving to deploying some of these use cases of production and then finally scaling AI as a core competency across so many different functions and departments I’ve helped so many companies go through that journey and I’ve seen different companies in different stages and I would love to share this expertise with you I would love to share some tips and tricks on
how to transition from each phase to the one after it I deeply believe we’re living in a very special moment right now when AI is really taking off it’s going to solve so many problems it’s going to make so many lives better and here’s the catch it’s not just for the teis everyone should be able to understand the essence of this amazing technology and be able to apply it in their day-to-day work and that’s the heart of that course it’s meant to be a non-technical introduction to non- AI
experts to help them really start their journey into this space without necessarily getting into the Integrity details of that field so with that said I really hope you enjoy the content of that course if you do I would appreciate if you share it with others who could benefit from.
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