ሰላም ቤተሰቦች!

እስኪ ደሞ አንዴ ትብብር!

ስለዚህ ቻናል አስተያየት ካላችሁ! የምትፈልጉትን ኮሜንት ላይ ፃፉልን!

ለቀጣይ ጉዞአችን አስፈላጊ ስለሆነ ነወ!..

የሚበረተታቱ ፤ መስተካከል ያለባቸውን ነገሮች ፤ ምን ላይ አጠናክረን መቀጠል እንዳለብን እና አጠቃላይ ማንኛውንም አስተያየት ብትሰጡን ደስ ይለናል።

🙏🙏

Good Morning!

#NewVideo

Are you:

👉A coding newbie lost in the web dev jungle?
👉A seasoned developer unsure where to specialize?
👉Just plain confused about all the career paths out there?


Fear not, Go to @EmmersiveLearning! YouTube Channel This video is your one-stop shop for navigating the exciting, but sometimes overwhelming, world of web development careers.



https://youtu.be/aKATCggAG9s

Burnout in Devs: It's Real!

🌱 Take Regular Breaks.
🕒 Set Realistic Work Hours.
🚶‍♂️ Incorporate Physical Activity.
🎯 Prioritize Tasks.
🤗 Ask for Help When Needed.

What are your strategies to avoid burnout? Share them here! 🔥🛑

GM Fams,

Microsoft Copilot is now in the palm of your hand - for FREE.

You can chat with Copilot, generate images with Dall-E, and more.

It's like having a creative sidekick on call 24/7.

Here's what it will do :
- Generate images with Dall-E 3
- Use GPT-4 conversations on the go
- Get web search results with Precise mode
- Unleash your creativity with Creative mode
- Chat through voice and take AI-enhanced photos


Learn how to use it in our YouTube Channel.
@EmmersiveLearning

Master Machine Learning:

The ML Tree 👇
|
|── Introduction to Machine Learning (ML)
| ├── Definition and Importance
| ├── Types of ML (Supervised, Unsupervised, Reinforcement)
| └── Applications of ML
|
|── Supervised Learning
| ├── Regression
| ├── Classification
| └── Model Evaluation Metrics
|
|── Unsupervised Learning
| ├── Clustering
| ├── Dimensionality Reduction
| └── Association Rule Learning
|
|── Reinforcement Learning Basics
| ├── Markov Decision Processes (MDP)
| ├── Rewards and Policies
| └── Exploration vs. Exploitation
|
|── Neural Networks and Deep Learning
| ├── Perceptron
| ├── Activation Functions
| ├── Multi-layer Perceptron (MLP)
| └── Convolutional Neural Networks (CNN)
|
|── Natural Language Processing (NLP)
| ├── Text Preprocessing
| ├── Tokenization
| ├── Named Entity Recognition (NER)
| └── Sentiment Analysis
|
|── Computer Vision
| ├── Image Processing
| ├── Feature Extraction
| ├── Object Detection
| └── Image Classification
|
|── Ensemble Learning
| ├── Bagging (Bootstrap Aggregating)
| ├── Boosting
| └── Random Forests
|
|── Model Evaluation and Selection
| ├── Cross-Validation
| ├── Bias-Variance Tradeoff
| └── Hyperparameter Tuning
|
|── Feature Engineering
| ├── Feature Scaling
| ├── Feature Selection
| └── Handling Categorical Data
|
|── Time Series Analysis
| ├── ARIMA (AutoRegressive Integrated Moving Average)
| ├── Exponential Smoothing
| └── LSTM (Long Short-Term Memory)
|
|── Anomaly Detection
| ├── Statistical Methods
| ├── Machine Learning Approaches
| └── Real-world Applications
|
|── Model Deployment
| ├── Flask API
| ├── Dockerization
| └── Cloud Deployment (e.g., AWS, Azure)
|
|── Explainable AI (XAI)
| ├── Local Interpretability Methods
| ├── Global Interpretability Methods
| └── Importance of Explainability
|
|── AutoML (Automated Machine Learning)
| ├── Automated Feature Engineering
| ├── Hyperparameter Optimization
| └── Model Selection
|
|── Bias and Fairness in ML
| ├── Types of Bias
| ├── Fairness Metrics
| └── Mitigating Bias in Models
|
|── Transfer Learning
| ├── Pre-trained Models
| ├── Fine-tuning
| └── Domain Adaptation
|
|── Time Series Forecasting
| ├── ARIMA (AutoRegressive Integrated Moving Average)
| ├── Prophet
| └── Neural Networks for Time Series
|
|── Reinforcement Learning Algorithms
| ├── Q-Learning
| ├── Deep Q Network (DQN)
| └── Policy Gradient Methods
|
|── Machine Learning with Scikit-Learn
| ├── Basic Usage
| ├── Data Preprocessing
| └── Model Training and Evaluation
|
|── Machine Learning with TensorFlow and PyTorch
| ├── Building Neural Networks
| ├── Training and Transfer Learning
| └── Deployment with TensorFlow Serving
|
|── Machine Learning in Industry
| ├── Healthcare
| ├── Finance
| ├── Marketing
| └── Manufacturing
|
|── Future Trends in Machine Learning
| ├── Federated Learning
| ├── Explainable and Ethical ML
| └── ML in Edge Computing
|
|── Machine Learning Community and Resources
| ├── Conferences and Journals
| └── Online ML Communities
|
|___ END __

Coding isn't just a skill. It's a superpower that unlocks endless possibilities in technology and beyond 💪🧙‍♂️

With coding, you can 👇👇

🤖 Automate tasks
💡 Solve problems
🚀 Create innovations
🎯 Increase career opportunities
🤲 Help other people to improve their lives

@EmmersiveLearning

Code the world!.

😳😢🤮🤮🤮

Could we use chatGPT then?

True ..right ?

😋😜🤗

CODE
CODE
CODE
CODE
CODE......

Consider a few points if you're a developer👇🏻

1. Create projects🗃
2. Read books📚
3. Read docs📃
4. Help others👨‍🏫
5. Daily coding👨‍💻
6. Be active in the community🐦
7. Internet surfing🌊
8. Learn daily💪🏻
9. Read latest tech blogs📖
10. Take short breaks🍻
11. Write notes✍️

@EmmersiveLearning

Learn Software Engineering

📚 Learn basics of programming
💻 Code daily for 100 days
🌐 Build small projects
🤝 Connect with coding communities
🚀 Showcase projects on GitHub
🎓 Explore online coding platforms
📝 Update resume/portfolio
🤖 Learn version control (Git)
🌐 Understand web development
🧠 Master a programming language
🧰 Build diverse skills (frontend, backend)
🛠 Use coding challenges
🚧 Contribute to open source
🌐 Create a LinkedIn profile
📱 Explore mobile app development
🌐 Network on social media
🎤 Attend virtual tech events
📝 Write technical blogs
📢 Share progress online
💼 Apply for freelance gigs
💰 Explore freelance platforms
🌐 Join coding forums
🎯 Set career goals
🚗 Keep learning and adapting
💼 Apply for entry-level jobs
🎉 Celebrate achievements
💡 Explore new technologies
📚 Read industry blogs/books
📝 Document your learning
💲 Start earning as a developer.

@EmmersiveLearning

🧠Coding in people's minds:

→Watch crash courses
→Build projects
→Get hired
→Done

🐙Coding in reality:

→Unsure what to learn
→Build projects
→Encounter roadblocks
→Apply for jobs
→Face rejections
→Persevere every day
→Keep showing up
→Finally get hired 🏆

@EmmersiveLearning