You’ll learn from Lynn’s long career as a technical educator, author, and consultant right from how she got started as a single mom, powered through by teaching herself programming and now is one of the world’s foremost educators on cloud and data technologies.

Lynn has also spent a number of years volunteering on technical projects with non-profits in Africa and giving talks at large conference gatherings in South Africa. She shares her perspective on the potential of Africa in the data economy, and so much more.

🧠 In this episode, you'll learn;

05:45 - Lessons from Lynn's career journey.

09:01 - Why Lynn decided to work on the cloud, data, and bioinformatics technologies.

14:22 - What Lynn’s time in Africa was like, during her years spent volunteering here.

17:06 - The promise Lynn sees in Africa in the data economy.

20:48 - Lessons learned as a technical educator.

25:15 - Her framework for delivering technical contents to make them accessible.

29:55 - How she manages her time between running her company, authoring contents, giving talks, and other engagements.

31:55 - The not-so-obvious reasons why an African Data Scientist should consider adopting cloud technologies.

34:58 - How you should approach learning Cloud technologies if you are on a budget.

36:38 - Her thoughts on the best Cloud vendor to adopt as a start-up in terms of cost and efficiency.

39:57 - Her best tips and practices for preparing for Cloud certifications.

42:07 - What the next big wave in Cloud tech that you should be aware of.

--

About Lynn Langit

Lynn Langit is a Cloud Architect who codes. She's a Cloud and Big Data Architect, AWS Community Hero, Google Cloud Developer Expert, and Microsoft Azure Insider. She has a wealth of cloud training courses on LinkedIn Learning. Lynn is currently working on cloud-based bioinformatics projects: LinkedIn, Twitter, GitHub.

--

LINKS MENTIONED IN THE EPISODE:

[October 2020] Please help African Data Scientists #EndSars by learning more here and supporting the online movement with the hashtag.

03:18 - Lynn's courses on LinkedIn Learning.

16:12 - Lynn’s workshop on “Essential Cloud Practices for Machine Learning and Data Science” here.

24:02 - About GitHub Codespaces.

25:02 - GitHub repo dedicated to learning cloud tech.

28:08 - MindMaps research here.

43:34 - TensorFlow Hub and TensorFlow responsible AI tools.

45:03 - GCP ML training on GitHub.

47:24 - Lynn's Microblog on Dev.to

Extra - Lynn's YouTube Big Data Playlist, Lynn's NPO Teaching Kids Programming.

--

🤝🏼Socials

Follow us on Twitter.

©2020 Port Harcourt School of AI. All rights reserved.

Natural Language Processing (NLP) is a hot area of research and application in the field of AI, but why should it matter to us as Africans? In this episode, we had a conversation with Salomon Kabongo KABENAMUALU, an NLP researcher at the African Master’s in Machine Intelligence (AMMI) which is a program under the African Institute for Mathematical Sciences (AIMS).

In this episode, you'll learn (with timestamps);

6:01 - What life is like as an African researcher. 

8:39 - What Natural Language Processing is and why it should matter to us as Africans.

11:49 - Why Salomon chose to make NLP research as opposed to other areas of technology.

14:36 - The current state of NLP technology in Africa.

17:26 - The challenges surrounding the progress of NLP for African problems.

20:45 - Salomon's prediction on how long it would take researchers to overcome the challenges halting the progress of NLP technology in Africa.

23:42 - Steps being taken to make NLP systems "responsible" for Africans.

 28:40 - Specific applications that NLP could be very optimal for that problems-solvers in Africa should be aware of.

32:00 - How these problem-solvers can leverage the *stable* progress in NLP and avoid getting caught up by the hype of the latest advancements.

35:35 - Pitfalls to avoid for African Data Scientists getting started learning and applying NLP to solve African problems.

39:40 - How global improvements in NLP in the coming years will affect how we apply the technology to solve African problems.

45:10 - Resources for Africans looking to learn more about NLP in the context of Africa.

--

Salomon’s;

>  LinkedIn

>  Twitter

>  Website

--

> Learn from one of our guest facilitator’s (Aurélién Geron) workshop on “Natural Language Processing in Action Using Transformers in TensorFlow 2.0” here.

--

LINK(S) MENTIONED IN THE EPISODE:

Mashanke NLP

Deep Learning Indaba

Professor Julia's episode Salomon referenced during the podcast here.

Speech and Language Processing (3rd ed. draft) by Dan Jurafsky and James H. Martin here.

--

> Subscribe, download, and if you enjoyed the show, leave a 5-star rating for us wherever you listen to your shows. It will help others find the show.

📩 Share with your friends and colleagues as well that will gain from this episode.

--

🤝🏼Socials

💙Follow us on Twitter.

📺 Visit our YouTube channel.

Becoming an AI entrepreneur is a very tricky endeavor and hence why you need to listen to this episode with Ankur A. Patel, an experienced AI entrepreneur.

Ankur A. Patel is currently the co-founder of a stealth-mode startup and the co-founder and managing partner at River AI Consulting, a boutique AI consulting practice to help organizations design and execute data strategies involving data science, machine learning, and data engineering. The portfolio includes work in computer vision, natural language processing, data normalization, anomaly detection, clustering, recommender systems, and predictive modeling.

You'll learn;

✅Ankur's career journey from college to co-founding AI startups and the most important difference between AI entrepreneurship and mainstream technology entrepreneurship.

✅ What made Ankur write the best-selling book "Unsupervised Learning with Python" and why he thinks unsupervised learning will gain more relevance than supervised learning soon.

✅ Ankur's thoughts on what it takes to build an AI startup and lessons he has learned from building AI startups and things that can be done differently.

✅ His best practices for building great machine learning products from unlabeled data.

✅ How to identify AI entrepreneurial opportunities and rule of thumb to identify problems that can be solved with AI.

✅ How African problem solvers can take advantage of the data (and potential for data) to solve problems for African and the key things to take note of like data governance and so on.

✅ How African problem solvers can come up with data and AI strategies that can help them effectively use these technologies to solve problems.

✅ Ankur's advice from a recruiter's perspective for people getting started in a career in Machine Learning and AI.

✅ Progress in applying AI with unlabeled data that entrepreneurs and practitioners should be aware of.

✅ Advice for problem solvers looking to apply unsupervised learning to solve real-world problems.

✅ What you should expect in the B2B space (business-to-business) with AI technology and intelligent document processing as a crucial technology for enterprise development.

--

Ankur's;

> LinkedIn

> Website

Learn from Ankur's workshop with our community on "Building Great Machine Learning Products With Unlabeled Data" here.

--

LINK(S) MENTIONED IN THE EPISODE:

You can purchase Ankur's best-selling book  "Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data" by clicking here.  Any purchase you make will support the efforts of the community. 💚💚

--

👍🏽 Subscribe, download, and if you enjoyed the show, leave a 5-star rating for us wherever you listen to your shows. It will help others find the show.

📩 Share with your friends and colleagues as well that will gain from this episode.

--

📍Some Articles on "Insights in AI and Data Science" Episodes You May Like from Experts and Practitioners:

Episode 5 - with Aurélien Géron, Former YouTube Product Manager.

--

🤝🏼Socials

💙Follow us on Twitter 🐦

📺 Visit our YouTube channel.

Do you know that some AI algorithms have pre-existing bias even without training data? What should you think about when you hear the term "Responsible AI"? We explore all of that and more in this episode with professor Julia Stoyanovich, an assistant professor of data science at the Center for Data Science at New York University (NYU). With both industry and academic experience, she is actively working in the domain of responsible data science and AI.

You'll learn;

⚫ Guest’s background (1:25) and lessons from career transition from industry to academia - 2:07.

⚫ What AI engineers and practitioners should think when they hear the term “responsible AI” - 4:36.

⚫ What the general public and non-engineers should think about in the context of responsible data science and AI - 7:02.

⚫ How human bias reflects in AI systems (8:55) and types of biases in computer systems - 12:10

⚫ Why AI algorithms are NOT neutral when it comes to bias in AI systems and examples of ways AI algorithms reinforces or introduces systemic biases - 13:01.

⚫ How Africa should go about adopting data privacy and protection measures - 16:16.

⚫ Breakthrough opportunities in responsible data science and AI for Africa and other underrepresented populations - 19:26.

⚫ Specific applications of AI we should pay attention to the most when applying responsible AI techniques - 21:25.

⚫ What people often get wrong about responsible AI and data science - 27:38.

⚫ Qualities you need to be a world-class AI researcher - 34:01

⚫ Guest's advice for you, if you are looking to build AI projects responsibly to solve real-world problems - 39:05.

--

Professor Julia's;

>  LinkedIn

>  Twitter

>  Website

> Learn from her workshop with our AI community on "Responsible Data Science, Privacy and Algorithmic Fairness" here.

--

LINK(S) MENTIONED IN THE EPISODE:

11:56 - The Paper Professor Julia referenced is "Bias in computer systems" by Batya Friedman and Helen Nissenbaum.

--

> Subscribe, download, and if you enjoyed the show, leave a 5-star rating for us wherever you listen to your shows. It will help others find the show.

📩 Share with your friends and colleagues as well that will gain from this episode.

--

📍Some Articles on "Insights in AI and Data Science" Episodes You May Like from Experts and Practitioners:

Episode 4 -  Sayak Paul, Google Developer Expert (GDE) in Machine Learning.

Episode 5 - with Aurélien Géron, Former YouTube Product Manager.

🤝🏼Socials

💙Follow us on Twitter 🐦

📺 Visit our YouTube channel.

Till next time. Take care, and be safe. 💚💚

Welcome, listener! In this episode, we had an enjoyable conversation with Dr Sebastian Raschka. This episode is packed with a lot of expert insights from Dr Sebastian on;

⚫ How he was able to come up with the idea of writing the best-selling Python Machine Learning book and what it takes to write a good book.

⚫ How to learn Machine Learning and the various ways to contribute to open source early on in your career.

⚫ How Universities in Africa can successfully adopt Data Science and AI to their educational curriculum, and how they can skill-up their lecturers and professors in AI and Data Science.

⚫ How small research labs in Africa just starting out can contribute something worthwhile to the ML community.

⚫ His advice for people starting to apply AI and Machine Learning to solve society's most challenging problems.

⚫ Progress and promise of Deep Learning and AI in Computational Biology, graph neural networks, and all other exciting areas.

⚫ The things that are changing in the fields of Machine Learning and AI in the next 3 years and the qualities you will need to become a world-class researcher in the fields of AI and Machine Learning.

We hope you enjoy this episode!

**************************************************************

Dr Sebastian's;

>  LinkedIn

>  Twitter

>  Website

> Learn from his workshop with our AI community on "Main Developments and Technology Trends in Data Science, ML and AI" here.

**************************************************************

LINKS MENTIONED IN THE EPISODE:

> Support the community's efforts by getting your copy of the best-selling Python Machine Learning through this affiliate link.

> Zindi.africa (Africa's Online Data Science Competition Platform).

> Dr Sebastian's Open Source Machine Learning software MLExtend.

**************************************************************

> Subscribe, download, and if you enjoyed the show, leave a 5-star rating for us wherever you listen to your shows. It will help others find the show.

📩 Share with your friends and colleagues as well that will gain from this episode.

> Some Articles on "Insights in AI and Data Science" Episodes You May Like from Experts and Practitioners:

Episode 4 -  Sayak Paul, Google Developer Expert (GDE) in Machine Learning.

Episode 5 - with Aurélien Géron, Former YouTube Product Manager.

Episode 6 -  with Emmanuel Okorie, Data Scientist at Maon Technology, and Formerly at Carbon (PayLater).

🤝🏼Socials

💙Follow us on Twitter 🐦

📺 Visit our YouTube channel.

Till next time. Take care, and be safe. 💚💚

Welcome, listener! In this episode, we had an enjoyable conversation with Dr Lee De Cola. This episode is packed with a lot of expert insights from Dr Lee on;

⚫ The potentials of spatial data analysis and geographic information systems (GIS) for an emerging Africa both for disruption and the continent’s sustainability.

⚫ He offered suggestions on what Africa can do to be independent of the Western countries technologically.

⚫ His life and career lessons as a retired federal researcher, professor of Geography, and have taught different age groups for decades.

He is a retired US federal researcher who served under the United States Geological Surveys department (USGS). He was also a professor of Geography at various colleges in the United States (including the University of Vermont). He was also a lecturer of political science at the University of Ibadan, Nigeria right after his PhD studies in the same University and was the foremost lecturer to introduce Applied Statistics to various departments at the University (of Ibadan).

Dr Lee spends most of his retirement time either doing data science, visualization, and spatial data analysis or playing music.

Dr Lee has also spent most of his time as a part-time instructor in various parts of the United States in topics like geographic information systems (GIS), spatial data analysis, and data science.

We hope you enjoy this episode!

**************************************************************

> Dr Lee's LinkedIn

> Dr Lee's Website (From Data to Insights)

> Learn from Dr Lee's practical workshop with our Community on R programming from the playlist here.

**************************************************************

LINKS MENTIONED IN THE EPISODE:

Links to some resources mentioned by Dr Lee Dee Cola in this episode:

> Fractal Analysis.

> Open Source GIS Software Options.

**************************************************************

> Subscribe, download, and if you enjoyed the show, leave a 5-star rating for us wherever you listen to your shows. It will help others find the show.

📩 Share with your friends and colleagues as well that will gain from this episode.

> Some Articles on "Insights in AI and Data Science" Episodes You May Like from Experts and Practitioners:

Episode 4 -  Sayak Paul, Google Developer Expert (GDE) in Machine Learning.

Episode 5 - with Aurélien Géron, Former YouTube Product Manager.

Episode 6 -  with Emmanuel Okorie, Data Scientist at Maon Technology, and Formerly at Carbon (PayLater).

🤝🏼Socials

💙Follow us on Twitter 🐦

📺 Visit our YouTube channel.

Till next time. Take care, and be safe. 💚💚

Welcome to another episode of "Insights in AI and Data Science" program where we get to get to learn from practitioners, researchers, enthusiasts nationally and internationally and know the thoughts on Artificial Intelligence, Data Science, and the potentials of these technologies for the African continent.

This episode features Robert John, the chief data scientist and Google Developer Expert (GDE) in Machine Learning and Cloud technologies, and in this episode, he discusses;

⚫ His career journey, troubles he faced and how he overcame them, 

⚫ The most important skills you need to succeed as a data scientist and machine learning engineer, 

⚫ The most important factors to consider in leveraging AI as a small company, 

⚫ And how AI can boost the growth of African countries including some brief case studies.

> Robert's Twitter

> Robert's LinkedIn

> Robert's Website (He has a new course on ML launching soon; register on the website)

> Learn from Robert's workshop on "Getting Started With Model Deployment" here.

LINKS MENTIONED IN THE EPISODE:

Links to some resources mentioned by Robert in the show:

> Arxiv unofficial Twitter bot for learning about interesting AI papers and keeping track of relevant advances.

> Arxiv official website here.

> Google Cloud APIs here.

> Subscribe, download, and if you enjoy it, leave a 5-star rating for us wherever you listen to your shows. It will help others find the show.

📩 Share with your friends and colleagues as well that will gain from this episode.

> Some Previous "Insights in AI and Data Science" Episodes You May Like from Experts and Practitioners:

Episode 4 -  Sayak Paul, Google Developer Expert (GDE) in Machine Learning.

Episode 5 - with Aurélien Géron, Former YouTube Product Manager.

Episode 6 -  with Emmanuel Okorie, Data Scientist at Maon Technology, and Formerly at Carbon (PayLater).

🤝🏼Socials

💙Follow us on Twitter 🐦

📺 Visit our YouTube channel.

Till next time. Take care, and be safe. 💚💚

Welcome to another episode of "Insights in AI and Data Science" program where we get to get to learn from practitioners, researchers, enthusiasts nationally and internationally and know the thoughts on Artificial Intelligence, Data Science, and the potentials of these technologies for the African continent.

This episode features Rising Odegua, a data scientist and researcher at Data Science Nigeria (DSN) and in this episode, he discusses his career journey, troubles he faced and how he overcame them, the most important skills you need to succeed as a data scientist and machine learning engineer, the most important factors to consider in leveraging AI as a small company, and how AI can boost the growth of African countries including some brief case studies.

> Rising's Twitter: https://twitter.com/risingodegua

> Rising's LinkedIn: https://www.linkedin.com/in/risingdeveloper/

> Learn from Rising's workshop on "Optimal Model Improvement With Data Preprocessing and Feature Engineering Workshop" here.

LINKS MENTIONED IN THE EPISODE:

Links to some resources mentioned by Rising in the show:

> Rising is the creator of the open-sourced Datasist library. Check it out here.

> Two-Minute Papers on YouTube for keeping yourself up-to-date in the field.

> Transcript and blog post for reading is not available for this episode yet. You may check back later.

> Subscribe, download, and if you enjoy it, leave a 5-star rating for us wherever you listen to your shows. It will help others find the show.

📩 Share with your friends and colleagues as well that will gain from this episode.

> Some Previous "Insights in AI and Data Science" Episodes You May Like from Experts and Practitioners:

Episode 4 -  Sayak Paul, Google Developer Expert (GDE) in Machine Learning.

Episode 5 - with Aurélien Géron, Former YouTube Product Manager.

Episode 6 -  with Emmanuel Okorie, Data Scientist at Maon Technology, and Formerly at Carbon (PayLater).

🤝🏼Socials

💙Follow us on Twitter 🐦

📺 Visit our YouTube channel.

Till next time. Take care, and be safe. 💚💚

Welcome to another episode of "Insights in AI and Data Science" program where we get to get to learn from practitioners, researchers, enthusiasts nationally and internationally and know the thoughts on Artificial Intelligence, Data Science, and the potentials of these technologies for the African continent.

This particular episode features Jeremiah Fadugba. He is a Teaching Assistant at the African Masters in Machine Intelligence and in this episode, he discusses his career journey, troubles he faced and how he overcame them, how Africa can leverage AI and Data Science for growth, and his advice for those searching for data science and AI jobs in Africa.

> Learn from Jeremiah's session on why classification algorithms work, and a teaser into deep learning here.

> Jeremiah's Twitter: https://www.twitter.com/jerofad

LINKS MENTIONED IN THE EPISODE:

What Jeremiah is excited about for the future of AI:

> self-supervised learning article from fast.ai here.

> Great answer on the difference between supervised learning, unsupervised learning, and self-supervised learning.

> More on self-supervised learning here.

> Learn about multimodal learning in this accessible article.

> www.paperswithcode.com

> Transcript and blog post for reading is not available for this episode yet. You can check back later.

> Subscribe, download, and if you enjoy it, leave a 5-star rating for us. It will help others find the show.

📩 Share with your friends and colleagues as well that will gain from this episode.

> Some Previous of "Insights in AI and Data Science" Episodes You May Like:

Episode 4 -  Sayak Paul, Google Developer Expert (GDE) in Machine Learning.

Episode 5 - with Aurélien Géron, Former YouTube Product Manager.

Episode 6 -  with Emmanuel Okorie, Data Scientist at Maon Technology, and Formerly at Carbon (PayLater).

🤝🏼Socials

💙Follow us on Twitter 🐦

📺 Visit our YouTube channel.

Till next time. Take care, and be safe. 💚💚

Welcome to another episode of "Insights in AI and Data Science" program where we get to get to learn from practitioners, researchers, enthusiasts nationally and internationally and know the thoughts on Artificial Intelligence, Data Science, and the potentials of these technologies for the African continent.

Our guest today is Vangelis Oden who is a Data and Machine Intelligence Engineer at Indicina technology, a Fintech startup that provides smart services for their clients. Vangelis shared insights about his life, education, career, qualities of a competent Machine Learning Engineer and Data scientist, challenges he has faced and how he overcame them. 

We were able to gain a lot of useful insights from him. This interview has lots of useful tips and best practices that can go a long way for you as you build your career in Data Science and Machine Learning.

What You Will Learn From This Episode?

> How Vangelis started a career and the challenges he faced, including how he overcame them.

> How small businesses can effectively come up with good data and AI strategy to work with, and why they shouldn't consider AI technology first.

> Qualities you should have to be a very good Data Scientist or Machine Learning Engineer.

> Why you should get started learning Data Science and AI now.

> How Machine Learning can improve sectors in African countries and what to take advantage of in the process.

> If you prefer to read this episode as a blog post, you can find it here (transcript included).

LINKS MENTIONED IN THE EPISODE:

What Vangelis is excited about for the future of AI:

Evolutionary Machine Learning: A great article to get you started with evolutionary machine learning here.

Generative Adversarial Networks: Ian Goodfellow is the creator of generative adversarial networks. You can learn how he came about it here.

Subscribe, download, and if you enjoy it, leave a 5-star rating for us. It will help others find the show. 

📩 Share with your friends and colleagues as well that will gain from this episode.

Some Previous Episodes of "Insights in AI and Data Science" Episodes You May Like:

Episode 4 -  Sayak Paul, Google Developer Expert (GDE) in Machine Learning.

Episode 5  - with Aurélien Géron, Former YouTube Product Manager.

Episode 6 -  with Emmanuel Okorie, Data Scientist at Maon Technology, and Formerly at Carbon (PayLater).

🤝🏼Socials

💙Follow us on Twitter 🐦

📺 Visit our YouTube channel.

Till next time. Take care, and be safe. 💚💚