No prior knowledge required
No unnecessary risks
Are you interested in pursuing a career in product management for AI and Data Science? If yes, then this course is undoubtedly the right choice for you!
Taught by Danielle Thé, a Senior Product Manager for Machine Learning, with years of experience in product marketing management for top tech giants like Google and Deloitte Digital, this course offers a unique opportunity to learn from an expert who has actually seen AI & data science implemented at the highest level.
In the past few years, organizational adoption of AI has grown significantly, with companies increasingly turning to big data and artificial intelligence to improve their operations and product offerings. With this growing demand for AI management, Product Managers have become the bridge between business needs and technically oriented data science and AI personnel. Therefore, organizations are looking to hire professionals like you who can lead them through this new and exciting change.
This beginner-friendly course has been designed to cover the fundamentals of the field, even if you are new to data science and AI, or if you don’t have prior product management experience. The course is structured into 12 sections, where we will start by introducing you to some key technological concepts for AI and data, distinguishing between data analysis and data science, and explaining the difference between an algorithm and an AI. We will guide you through different types of machine learning, and an overview of the role of a product manager and the difference between a product and a project manager.
When you reach section 3, we will discuss business strategy for AI and Data, including performing a SWOT analysis, building, and testing a hypothesis. We will then focus on User experience for AI & Data, getting the core problem, user research methods, developing user personas, and approaches to AI prototyping. We will also teach you how to source data for your projects and the type of data that you need when working with different machine learning.
In sections 6, 7, 8, and 9, we will examine the full lifecycle of an AI or data science project in a company, from product development to model construction, evaluating its performance, and deploying it.
Sections 10, 11, and 12 will guide you on how to manage data science and AI teams, improve communication with team members and make necessary remarks regarding ethics, privacy, and bias.
A career as a Product Manager is not only exciting but also well paid, secure, and offers ample opportunities for growth and promotion. According to Glassdoor, the average salary for a product manager is $108,992 per year.
So What are you waiting for? Subscribing to this course is the best decision you will make today to distinguish yourself from others and set your foot on the path to a successful career as a product manager for AI and data science!
