AI for Leaders: A Practical, No-Code Intro to Machine Learning and Deep Learning
Learn about what AI, ML and DL are, and how you can use each to grow the bottom line - in plain English.
AI for Leaders: A Practical, No-Code Intro to Machine Learning and Deep LearningGET IN TOUCH
What will I learn?
Separate the value from the hype.
Understand what types of problems data science and machine learning can help solve.
Understand the different roles in the data science ecosystem.
Find and vet the right candidates for each role.
Learn how to check your data scientists’ work for accuracy, even if you are not technical.
Identify and avoid project pitfalls.
Manage the machine learning process.
Ensure that your data science and machine learning projects are always delivering value.
AI in a Nutshell
Learn the difference between analytics, data science, machine learning and AI. Understand how AI is being deployed by businesses right now, and how it will change in the future. Learn how to cultivate a data-driven organization.
Doing AI: Who Does What In The AI Ecosystem
Learn about different roles in AI, what tools they use, and how to find and hire the right candidates for each.
Managing the ML and AI Processes
Learn about different types of business questions your organization can answer with machine learning and AI. Identify which tasks and processes can be efficiently automated using AI. Learn how to manage the process.
AI In The Trenches: What Could Go Wrong And How To Fix It
Learn how to get started with AI/ML in your organization, and how to measure and communicate the success of a project.
Learn from an elite team of industry experts who have taught at universities such as Harvard, and have trained teams at companies such as Qualcomm.
We customize training content to match your team's goals. During training, your team works on projects that are relevant to your business.
All our trainings involve in-class, hands on practice that is relevant to your team's goals. At the end of the training, your team will be ready to hit the ground running.
On site and live online
Choose whether you prefer in-person training, or you need the online participation of a geographically distributed team.
Frequently Asked Questions
1. Who is this course for?
This course is aimed at team leads, managers and executives interested in understanding what data science, machine learning and deep learning are, the roles associated with projects using them, and how success is measured. Whether you are tasked with building a data science team from scratch, or just beginning to assess the potential benefits of data science and machine learning for your organization, this workshop is for you.
2. Is this a MOOC (Massive Open Online Course)?
Absolutely not. Unlike other internet courses, this course is completely live. Your instructor lectures in real time (either on-site, or live on-line) and can answer questions and provide real-time, tailored feedback so you can reach your goals as fast as possible. At Edlitera, we believe nothing beats the experience of learning live from an elite instructor with extensive industry experience.
3. What is the format of this course?
The course combines lecturing, hands-on exercises to be solved both individually and in pairs, as well as one or two larger projects that require participants to use their newly acquired knowledge to solve real-world problems.
Exercises and projects are chosen to be relevant to the type of problems that your team encounters daily. Our goal is to deliver practical, immediately applicable knowledge, and to empower your team to hit the ground running after each training. Our instructors can teach this course on site at your offices or live online.
4. Can you tweak the content of the course for my team?
Of course! While we do offer a standard version of this course, we can also work with you to tailor the content such that it fits your team's priorities perfectly.
5. What if I have other questions?
If you have other questions, or want to find out more about this course or other courses we offer, please ping us - we love questions! You can email us at [email protected], or get in touch via the chat box below.