ChEngrg.๐จโ๐ญ| Data & Al - Excel. PowerBI. SQL. Python. | 2D Motion Designer| @Arsenalโค๏ธ
Joined May 2024
- Tweets 2,520
- Following 322
- Followers 357
- Likes 6,056
106 Photos and videos
Pinned Tweet
Published my first SQL project on GitHub & Google Drive.
๐คโบ๏ธ
(85% MySQL 15% MS Excel)
Now, I know the reason why building projects are valued more than just watching tutorials.
It took me about a week to pull this off.๐คง
PROJECT TITLE: THE STATE OF CONTENT WRITING IN NIGERIA: A DATA-DRIVEN INSIGHT ๐โ๏ธ
I recently completed a data analytics project exploring the current landscape of content writing in Nigeria using survey data from 103 Nigerian content writers across..
#DataAnalytics #SQL #DAI
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๐ป๐๐๐๐๐๐๐ฎ๐ป๐ ๐งกโค๏ธ๐ retweeted
Late last month, I successfully passed my Chemical Engineering Doctoral Candidacy Exam (DCE) at the University of Michigan.
God has been truly faithful, and I am deeply thankful for His unending grace. I am grateful to have reached this first major milestone on my PhD journey.
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I went through the quotes, and I must say that there are still ladies with the zeal to succeed greatly in their respective fields.
That's inspiring ๐ฏ
Jun 12
Hi women, can you post pictures or talk about your academic achievements? I need some motivation this month.
If you see this tweet, share it so women can see it.
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With the opportunity provided by @DataCamp and @nithub_lag, I've been able to secure these certs, as a way of improving my knowledge on Python for data analytics and data science.
Introduction to Python programming consists of ..
#DataAnalytics #DataScience #Python #DataCamp
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Python variables & types, lists, functions & packages, Numpy and numpy arrays.
Intermediate Python went further to teach basic plots wt Matplotlib, dictionaries & pandas, logic, control flow and filtering, loops (while, for & data structures), random numbers.
Off to projects ๐
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Quick Reminder โฐ:
AI is a mirror.
If your inputs are vague, generic, and lazy, your outputs will be exactly the same.
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One of my biggest surprises in life is the ability of an individual to predict a near-perfect event.
And, today made is 100% perfect.
I've seen it countless times on X.
Do these guys study data, patterns, read charts, solve statistics, mere guesses or probably wizardry, lol.
15 May 2020
Iโd bet on Elon Musk being a trillionaire before Jeff Bezos, just wait till Elon make humans a multi planetary species.
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Learning Python for Data fields is very tasking.
The good side of a good knowledge in Python, is that you can navigate through different tech parts with it.
In fact, it makes transitioning easier.
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A lot of things I had to leave.
Decisions I took, for a purpose.
God see me through ๐
Jun 10
Get into the habit of asking yourself honestly, "Does this support the life I am trying to create?" If not, release it.
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๐ป๐๐๐๐๐๐๐ฎ๐ป๐ ๐งกโค๏ธ๐ retweeted
MT Scholar Chinaecherem Anyanwu Earns Master's Degree from University of Michigan
We proudly congratulate 2024 MT Scholar, Chinaecherem Anyanwu, on earning his Master's degree in Chemical Engineering from the University of Michigan.
Chinaecherem previously graduated with First-Class Honors in Chemical Engineering from the Federal University of Technology, Owerri, achieving an outstanding CGPA of 4.88/5.00.
His journey reflects the power of hard work, academic excellence, and a commitment to continuous growth.
Congratulations, Chinaecherem! The entire MT Scholarships community is incredibly proud of your achievement and excited for what lies ahead.
Now, let's go bag that PhD.
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Data science requires the intersection of coding skills, mathematical/statistical knowledge, and domain expertise.
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Experimentation in data fields follows these processes:
Question formation
Hypothesis formation
Data collection
Hypothesis testing with stats
Data interpretation
Reporting and Interactions are possible additions.
#DataAnalytics #DataScience
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Learnt from @DataCamp, that Subplots in Matplotlib are multiple plots arranged in a grid within a single figure e.g. a 2ร2 grid gives you 4 separate charts side by side.
Notable applications of Subplots include:
#DataAnalytics #dataScience #Python #nithub
In the @DataCamp 'Intermediate Python' course, I came across Matplotlib.
Matplotlib is a Python library for creating charts and graphs.
Use colour picker to get the HEX codes of colours.
Still learning, still improving.
Gmโจ
#DataAnalytics #dataScience #Python #nithub
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โจ Data comparisn:
Researchers use subplots to show different variables or conditions side-by-side.
โจ Time-series analysis:
Allow visualizatn of different time intervals or sensor outputs in engineering and finance.
โจ Model evaluation
In ML, subplots are used to compare
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training vs. validation performance, or feature importance.
โจ Scientific experiments:
Research papers often use subplots to present simulations or parameter sweeps in one figure.
โจ Survey results
Social sciences employ subplots to display demographic breakdowns or correlations
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๐ป๐๐๐๐๐๐๐ฎ๐ป๐ ๐งกโค๏ธ๐ retweeted
30 Nov 2022
today we launched ChatGPT. try talking with it here:
chat.openai.com
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Negative constraints are capable of doing magic in AI/ LLM prompting.
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In the @DataCamp 'Intermediate Python' course, I came across Matplotlib.
Matplotlib is a Python library for creating charts and graphs.
Use colour picker to get the HEX codes of colours.
Still learning, still improving.
Gmโจ
#DataAnalytics #dataScience #Python #nithub
Just finished my practice in Numpy Basic Statistics:
-Converting lists to arrays e.g np.array([ ])
-Extracting data columns for analysis
-Calculated median & mean with np.median(), np.mean()
-Using np.corrcoef() for correlatn and np std() for standard deviatn
#datacamp #Python
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๐ป๐๐๐๐๐๐๐ฎ๐ป๐ ๐งกโค๏ธ๐ retweeted
How to get lucky in life
1. Build skills that make you useful. Luck rarely sticks to people who cannot capitalize on it.
2. Say yes to invitations that stretch you, even when they feel inconvenient or uncomfortable.
3. Show up early, follow up often, and keep your name in rooms where decisions are made.
4. Treat every interaction like it matters, because luck often arrives disguised as a person.
Luck is not magic. It is simply your exposure multiplied by readiness.
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One specific thing I've learnt during the course of my learning AI integration & Prompt engineering is that:
Prompting is just programming in natural language. If you canโt explain a task to a human clearly, you can't prompt an AI to do it.
Good morning โจ
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