I was at DevFest 2021. I met a lot of amazing tech bros and sis...after tge meet and greet we had to snap group picture . Each time I zoom in on the pic, I can still see myself and a lot of tech bro and sis that i connect with back then.

For anyone starting out in data: focus on these 3 first. I notice these skill would give you clarity, confidence, and a portfolio recruiters actually understand. I would be sharing my personal journey keep tab open..

<<< learning +problem solving==💯💯

#buildinpublic

Just finished my pivot table and analysis, then added a slicer to make the dashboard responsive. It was a bit calculative, but totally worth it! #Excel #PivotTable #Dashboard #LearningByDoing

dataset was shared by Adewale Yusuf in his YouTube tutorial; it was already cleaned, which made things easier. I combined it with what I learnt in class,

Last weekend during Excel Friday with @ahmed_onchain, we were introduced to dashboards. I decided to give it a shot using what I learnt in class and a tutorial by @Adewaleanalyst

@omoalhajaabiola @skill_afrika_ One of my lifetime goals is to successfully build a platform to simplify aerospace engineering for aspiring engineers and make learning much more captivating for students and enthusiasts alike.. We're going to achieve this through @_Symplified

Still in the business of creating high quality shoe and footwears..

Hey everyone! 👋 I'm really excited to be joining the Fitech Web3 Bootcamp! For me, it’s more than just a bootcamp — it’s a chance to learn, grow, and i think is time I be part of a community that’s passionate about Web3 and data science. 👉 https://t.co/0mfEyW2xVT

Week 1 of learning AI|ML|Data science Link to the GitHub repo https://t.co/TqEb1kr13y

Data visualization – because charts tell better stories! 📊 I used seaborn to explore patterns: Survival by class 🏷️→ First-class passengers had a higher survival rate. Survival by gender 🚻→ More women survived than men. Age vs. survival ⏳→youth had better chance of survival

had to clean the data because of some missing parameter and category them so as to fill the missing values

imported the necessary libraries: 🔹 pandas 🔹 seaborn 🔹 matplotlib used Seaborn to load the Titanic dataset and to get a quick preview, I used df.head() This displayed the ✅ Passenger class (class) ✅ Gender (sex) ✅ Age (age) and other features and observation

Weeks 1 & 2 of #3MTT Training – AI & ML I missed some sessions, so I caught up with the recordings. To put what I learned into practice, I explored the Titanic dataset—and wow, the insights were mind-blowing! 😲 Here’s how it went. 🧵👇

It’s not just about learning a skill Beyond all the tutorials. To break out even,I need to start learning to solve real problem to leave a lasting impact . Problem solving is a skill that should be learnt daily GM and Have a productive week ahead

Join in: WHY CONSISTENCY BEATS TALENT https://t.co/nIIRucHGkW

Guess who won a merch....@gdg_kaduna @Fitechcommunity #devfestkaduna #DevFest2024 Thank you @Fitechcommunity got a lot of value from yesterday session🚀🤍.

30-for-30 Do something for 30 minutes in 30 days - Choose a skill - Commit to doing it for 30 minutes in 30 days - Find your accountability partner in the comment section Track your progress Are you in?

Hello tech twitter...it my birthday wish me well...