π₯ Let's call today's post "From Red to Green" ππ«‘
In yesterday's Day 5 post, I got stuck with an error where Telethon was running inside Dagster, causing session file conflicts that crashed the pipeline.
After many hours of debugging, I finally solved all the issues, and the pipeline is now running successfully, as you can see in the images. That's what happens when consistency pays off. It was really overwhelming, but sometimes all you need is a short break before the solution becomes clear. ππ
And finally, this week's project has come to an end. All that's left now is the report and presentation. π€π€
#Day6
In yesterday's Day 5 post, I got stuck with an error where Telethon was running inside Dagster, causing session file conflicts that crashed the pipeline.
After many hours of debugging, I finally solved all the issues, and the pipeline is now running successfully, as you can see in the images. That's what happens when consistency pays off. It was really overwhelming, but sometimes all you need is a short break before the solution becomes clear. ππ
And finally, this week's project has come to an end. All that's left now is the report and presentation. π€π€
#Day6
π5
If you noticed, 2026 backwards is 6202 and if you take away 6 and 2, you will have 02.
It doesn't mean anything but Thanks for reading.πππ
Good night π΄ π₯± Don't foregt to have a restπ€πͺ
It doesn't mean anything but Thanks for reading.πππ
Good night π΄ π₯± Don't foregt to have a restπ€πͺ
π3π’2
Finally the final day comes ππ
Writing a report is actually the most overwhelming .As I said in past week it helps me to exercise how can I express my technical work to non technical teams in plain english .
I don't know how the week move fastππ½ββοΈ like this π€¦π½ββοΈI built a full end-to-end data engineering pipeline scraping Telegram channels, building a data warehouse with dbt, detecting objects in images with YOLO, exposing insights through a FastAPI, and orchestrating everything with Dagster. All in one week. π€πΎ
At the start, words like "star schema", and "Dagster" felt like a foreign language. The debugging sessions were real. ππ But every error was a lesson and every fix made the system stronger.
Just start, stay consistent, and keep building. πͺπΎ
#DAY7
Writing a report is actually the most overwhelming .As I said in past week it helps me to exercise how can I express my technical work to non technical teams in plain english .
I don't know how the week move fastππ½ββοΈ like this π€¦π½ββοΈI built a full end-to-end data engineering pipeline scraping Telegram channels, building a data warehouse with dbt, detecting objects in images with YOLO, exposing insights through a FastAPI, and orchestrating everything with Dagster. All in one week. π€πΎ
At the start, words like "star schema", and "Dagster" felt like a foreign language. The debugging sessions were real. ππ But every error was a lesson and every fix made the system stronger.
Just start, stay consistent, and keep building. πͺπΎ
#DAY7
π₯6
Forwarded from BΟ
ΙΎΤΞ±Ι³-Ops (BΟ
ΙΎΤΞ±Ι³ | Ψ¨Ψ±ΩΨ§Ω :))
you could truly learn anything and thatβs the beauty of it!
β€4
Never undervalue the blessing that God has given us health and air to breathe!
Always be grateful.βΊοΈππΎ
#simruthoughtsπ
Always be grateful.βΊοΈππΎ
#simruthoughtsπ
β€4π1
I honestly couldn't have imagined reaching this level when I first started. Back then, I told myself, "Letβs just start and see what happens."ππ
Seeing our hub like this βΊοΈmakes it all feel real. It's happening, and there is so much more growth and learning to come! π
Huge shoutout and credits to @atocodes for pointing this out and showing me how much progress I've actually made. Thank you! π
Seeing our hub like this βΊοΈmakes it all feel real. It's happening, and there is so much more growth and learning to come! π
Huge shoutout and credits to @atocodes for pointing this out and showing me how much progress I've actually made. Thank you! π
β€5π1
πJuly 1 is a reminder that we've made it halfway πͺβ¨ through 2026/2018 E.C .and we still should keep going . May the rest of the month of this year be soft, kind and everything we've hoped for!!!πβ¨
π΄Goodnight everyone! Don't forget to rest and drink water
π΄Goodnight everyone! Don't forget to rest and drink water
β€6π1
Forwarded from AAU NEWS
π’ Training Update: Registration is Still Open!
Due to a schedule update, our FREE 3-Day Online Training on Data Analytics & Visualization Using Python will now take place on July 6β8, 2026.
If youβre looking to build practical skills in data analysis, data cleaning, and data visualization using Python, this training is for you!
π July 6 β 8, 2026
π Online | English
π Certificate upon successful completion
β 100% attendance required
The training is open to anyone committed to learning. All you need is a laptop, a stable internet connection, and the dedication to participate throughout the program.
π Registration is still openβdonβt miss your chance to join!
π Register here: https://forms.gle/9mH1jg5AjRXwLXwh7
Due to a schedule update, our FREE 3-Day Online Training on Data Analytics & Visualization Using Python will now take place on July 6β8, 2026.
If youβre looking to build practical skills in data analysis, data cleaning, and data visualization using Python, this training is for you!
π July 6 β 8, 2026
π Online | English
π Certificate upon successful completion
β 100% attendance required
The training is open to anyone committed to learning. All you need is a laptop, a stable internet connection, and the dedication to participate throughout the program.
π Registration is still openβdonβt miss your chance to join!
π Register here: https://forms.gle/9mH1jg5AjRXwLXwh7
π3
β‘οΈπ₯This week I will work on a Time Series Forecasting for Portfolio Management project for some Investments! I'll use historical financial data (Tesla, Bonds, and S&P 500) to predict market trends and help optimize an investment portfolio.
Who is this for?
π Financial analysts and investors who want data-driven insights instead of guesswork when building a portfolio.
The system will answer real questions like:
π What are the future market trends?
βοΈ How do we balance high risk (Tesla) vs stability (Bonds) vs diversification (S&P 500)?
πΉ What's the optimal investment mix for the best return with the least risk?
π Would this strategy have actually worked if tested on past data?
I will learn ARIMA/SARIMA models, LSTM (deep learning for forecasting), Modern Portfolio Theory, and backtesting strategies using Python.
I will start working on this today updates coming soon! π
Who is this for?
π Financial analysts and investors who want data-driven insights instead of guesswork when building a portfolio.
The system will answer real questions like:
π What are the future market trends?
βοΈ How do we balance high risk (Tesla) vs stability (Bonds) vs diversification (S&P 500)?
πΉ What's the optimal investment mix for the best return with the least risk?
π Would this strategy have actually worked if tested on past data?
I will learn ARIMA/SARIMA models, LSTM (deep learning for forecasting), Modern Portfolio Theory, and backtesting strategies using Python.
I will start working on this today updates coming soon! π
π₯4
π₯ #DAY1 on the portfolio optimization project
Today I focused on understanding the project before touching any code, and honestly, a lot of new finance concepts hit me at onceπ€ππbut I try to manage it.
What I Have done and learn today:
Pulled historical data via YFinance and cleaned missing values
π Explored trends, volatility, and outliers through visualizations
π§ͺ Ran stationarity tests (ADF) prices are non-stationary, returns are stationary
β οΈ Calculated risk metrics VaR and Sharpe Ratio for all 3 assets
Struggle of the day: finance terms were genuinely new to me, try to understand by using simple real-life analogies just to get the concepts to startβ‘οΈβ‘οΈ
Day2 will be on the forecasting models π₯π₯
And also don't forget to take hydration breakππ
Today I focused on understanding the project before touching any code, and honestly, a lot of new finance concepts hit me at onceπ€ππbut I try to manage it.
What I Have done and learn today:
Pulled historical data via YFinance and cleaned missing values
π Explored trends, volatility, and outliers through visualizations
π§ͺ Ran stationarity tests (ADF) prices are non-stationary, returns are stationary
β οΈ Calculated risk metrics VaR and Sharpe Ratio for all 3 assets
Struggle of the day: finance terms were genuinely new to me, try to understand by using simple real-life analogies just to get the concepts to startβ‘οΈβ‘οΈ
Day2 will be on the forecasting models π₯π₯
And also don't forget to take hydration breakππ
π₯3
Good night fams π΄π΄
Everyday begins with expectations and
ends with experienceπ
β€2
Forwarded from TechVibe
If you're not tired of rejecting me, I won't be tired of applying. π
GN gangβοΈ
@devwitheyob
#TechVibe #jobs #LinkedIn
GN gangβοΈ
@devwitheyob
#TechVibe #jobs #LinkedIn
π2