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Black and Brilliant AI Accelerator: Meet the Coaches

The Black and Brilliant AI Accelerator kicked off in March, and we’re excited to share a look behind the scenes. We’ll share a recording of the introductory session and introduce you to some of the coaches. Plus, we’ll share a sneak peek at what’s to come for the learners in the program, several of whom we introduced you to last month.

To kick off the session, hosted over Zoom on March 15, Tony Effik, who co-founded Black and Brilliant with Perky Noah-Effik, shared the inspiration behind Black and Brilliant — and this accelerator program. “We believe that with the right kind of support, with the right kind of training, and with access to networking and resources, a new generation of Black and Brown people from around the world can enter leadership roles across industries.”

Meet the coaches

The learners in the accelerator program will be making their way through the Data Scientist Career Path on Codecademy. They’ll also be working with a collection of expert coaches to explore responsible AI, social justice, and bias in machine learning.

While much of the mentorship and coaching will be one-on-one with the learners, there will be recordings shared throughout the duration of the program. So feel free to make your way through the course on your own and follow along for video updates from The Black and Brilliant Advocacy Network on LinkedIn.

In the introductory session, we got to meet many of the coaches, whom you can learn more about below. These coaches understand the industry from all different angles — some have technical knowledge, others come from academia, and their backgrounds span everything from AI to data science, research, and design.

Mahir Yuvaz

Mahir Yuvaz has a background in product development and data science. He formerly ran the data science team at RGA, co-founded Topos, and is currently the Director of Engineering at Etsy.

“Data science and machine learning-related roles are still heavily a work in progress in the industry,” he says. “They are not well-defined in some organizations.” Mahir will be sharing his experience in navigating those ambiguities with accelerator program participants.

Yla Eason

Yla Eason has a background in Learning and Development and is currently an Assistant Professor of Practical Practice at Rutgers. Yla joins the AI Accelerator to provide career coaching to participants.

“The hard skills will get you hired and the soft skills will get you fired,” she says. Yla stresses the importance of street smarts, how to navigate having crucial conversations, how to present yourself, and business communication. She also teaches search engine marketing and digital marketing.

Michael Horn

Michael Horn is the Chief Data Officer at Huge, a product and digital experience design company. Michael is also co-author of a Data Practices Manifesto in partnership with The Linux Foundation and data.world.

The manifesto, Michael shared on the introductory call of the accelerator program, “looks at principles as a function of values — personal values, corporate values, and employment values — and making sure that everything we do as data professionals is guided by a code of practices that is defensible today as well as to our future selves when things are not such a Wild West as they are today.”

Marc Maleh

Marc Maleh is GVP Emerging Experiences at Huge. His background is in the intersection of technology and design and he works as an adjunct professor at NYU where he taught a class on designing with artificial intelligence.

Mark is interested in the intersection of humanizing data, humanizing technology, and will be coaching accelerator participants on how they can position the work that they’re doing in their careers.

Nana Essuman

Nana Essuman is the Director of Data Engineering at Condé Nast and has joined the AI Accelerator as a mentor to help participants figure out how to get data into their projects.

Nana shares that one thing that doesn’t get emphasized when you’re a data scientist is that once you finish building your models you need to move them into production. His expertise will help learners get their data to a point where they can start doing feature engineering on top of their models.

Valarie Embrey

Valarie Embrey is a Masters student at Rutgers School of Business as well as a VP on the Institutional Technology team at Citibank. Valarie will be providing career coaching and mentoring participants when it comes to increasing the performance of teams.

Ruth Ikwu

Ruth Ikwu is a Research Associate at Cardiff University’s Center for Cyber Security Research and works as a data engineer. She explains, “60-80% of data science projects are going to be getting and clearing your data.” She’ll be available to help participants with this, along with social network analysis.

Femi Anthony

Femi Anthony is a Lead Data Engineer at Capital One. In the intro session, Femi touched on the demand for data engineers vs. data scientists. “It’s one thing to create the model in Jupiter Notebooks,” he says. “But actually getting it into production is where you need the data engineers — to actually scale and get the model running every day with very little trouble.” Femi will be available to help mentor participants in this area.

Bashir Mohammed

Bashir Mohammed is a Postdoctoral Research Fellow at Berkeley Lab, working on a postdoc in Deep Learning and Artificial Intelligence High-Performance NEtworks (DAPHNE). He’s also an experienced AI and Machine Learning Engineer.

Bashir touched on why clearing and processing data is so important. “Good data leads to good results,” he says. Bashir also shares an introduction to AI and Machine Learning in the 8-minute video below.

Sakinah Adebola Abdul-Ibiyeye

Sakinah Adebola Abdul-Ibiyeye works at Paypal in Dublin and has joined as a mentor to support participants looking to develop projects related to payment, including fintech and e-commerce, as well as cloud security.

Quincy Olatunde

Quincy Olatunde is VP Data Product Management at NBCUniversal Media. While he has a background in programming and technology, he works more on the business side now.

“I’m a product person who understands data,” Quincy says. He’ll be available to help participants take data and turn it into meaningful insights and storytelling to share with consumers.

Alexander Liss

Alexander Liss is Head of Data Science and Analytics at Wunderman Thompson. Alexander uses ML and analytics to turn business problems into opportunities for innovation and growth, and his long-term vision is to use AI & ML for double-bottom-line impact on both social good and business profit.

Alexander shares an introduction to Supervised Learning in the video below.

Tokunbo Michael Hiamang

Tokunbo Michael Hiamang is a data scientist and semantic engineer, specializing in Natural Language Processing (NLP) at Memorial Sloan Kettering’s Cancer Research Center. Tokunbo was unable to make the official kickoff meeting but shared the following video for learners on NLP.

Steve Kaneti

Steve Kaneti is a Senior Data Engineer at DoubleVerify with experience turning research and initial concepts into consumer-facing products in both the hardware space and SAAS space.

What’s coming next?

As we mentioned above, in addition to learning on Codecademy, participants will be diving into topics including UX, Responsible AI and Social Justice, and the Business of AI. We’ll share updates in the coming weeks, but here’s a sneak peek of what you can expect, described by Tony Effik:

  • User Experience: In the world of data science, you'll need at minimum to present data through infographics and data visualization, but you might also be called upon to work in situations where you are building platforms and applications that require UX design, user research, and creativity. Learners will explore these topics and prepare for working in that world.
  • Responsible AI and Social Justice: We want our learners to be a new voice in the room in the world of AI. That means being proponents of Responsible AI and Transparency, helping the industry develop best practices for the AI industry by reducing systemic injustices and furthering equality. That will manifest in many ways but will include data literacy and equality, consent in user experiences, and ethical practices in marketing.
  • The Business of AI: This accelerator course is meant to serve as on ramp into the world of AI. This workstream of the program will provide all the “cheat codes” for starting a successful career. We believe so much of today’s success is the soft skills and understanding how the business is structured, how it works, and how to navigate, network and collaborate with people in the industry. We’ll help our learners discover the cheat codes and map the business for them.

We’ll be back with more updates here on the Codecademy blog. In the meantime, follow The Black and Brilliant Advocacy Network on LinkedIn to stay in the loop!

Get more practice, more projects, and more guidance.

Black and Brilliant AI Accelerator: Meet the Coaches
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