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Google has launched 33 courses with free certificates. No payment is required! Here are the top courses:
1. Google JavaScript Promises Courses
2. Google Developing Android Apps
3. UX Design for Mobile Developers
4. Max MSP Programming Course
5. Machine Learning Specialization
6. to Data Science with Python
7. CS50βs to Artificial Intelligence with Python
8. CS50βs Web Programming with Python and JavaScript
9. Circuits and Electronics 1
10. Supply Chain Analytics
You Should Know:
Here are some practical commands and codes related to the courses:
Python for Data Science
import pandas as pd
data = pd.read_csv('data.csv')
print(data.head())
JavaScript Promises
[javascript]
let promise = new Promise((resolve, reject) => {
let success = true;
if (success) {
resolve(“Promise fulfilled!”);
} else {
reject(“Promise rejected!”);
}
});
promise.then((message) => {
console.log(message);
}).catch((error) => {
console.log(error);
});
[/javascript]
Linux Commands for Developers
<h1>Check system information</h1> uname -a <h1>List running processes</h1> ps aux <h1>Search for a file</h1> find / -name "filename" <h1>Monitor network traffic</h1> sudo tcpdump -i eth0
Android Development
<h1>Build an APK</h1> ./gradlew assembleDebug <h1>Install APK on a connected device</h1> adb install app-debug.apk <h1>Logcat for debugging</h1> adb logcat
Machine Learning
from sklearn.model_selection import train_test_split from sklearn.linear_model import LinearRegression <h1>Load dataset</h1> X, y = load_dataset() <h1>Split data</h1> X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2) <h1>Train model</h1> model = LinearRegression() model.fit(X_train, y_train) <h1>Predict</h1> predictions = model.predict(X_test)
What Undercode Say:
These courses are a goldmine for anyone looking to upskill in tech. Whether you’re diving into Python for Data Science, exploring JavaScript Promises, or mastering Machine Learning, these free resources are invaluable. Pair them with practical commands like Linux system monitoring (tcpdump, ps aux) or Android development tools (adb, gradlew) to solidify your learning. Donβt forget to experiment with Python libraries like `pandas` and `scikit-learn` for hands-on experience. Happy learning! π
References:
Reported By: Shubhangi Shrivastava – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass β



