AI Engineering Course
What will I learn?
በዚ ኮርስ ምህንድስና AI (AI Engineering Course) ተሞክሮኻ ኣብ ቴክኖሎጂ ኣዕብዮ። እዚ ኮርስ'ዚ ንባዓል ሞያ ቴክኖሎጂ ዝተዳለወ ኮይኑ፣ ን AI ብዝበለጸ ንምልላይ ዝሕግዝ እዩ። ከም Recall, F1-Score, ከምኡውን መስርሕ ምምልካት (cross-validation) ዝኣመሰሉ ኣገባባት ገምጋም ሞዴል ብዕምቀት ክትመሃሩ ኢኹም። ብውጽኢታዊ መንገዲ ከመይ ጌርካ ኸም እትጽሕፍ ክእለትካ ኣመሓይሽ፣ ከምኡውን ንትንበያ ምዝባዕ (churn prediction) ዝጠቅሙ ኣልጎሪዝም ማሽን መሃሪ (machine learning algorithms) ዳህስስ፣ እንተላይ ውሳኔታት ኣግራብ (decision trees) ከምኡውን ሎጂስቲክ ርገረሽን (logistic regression)። ኣብ ዳህሳስ ዳታ (data exploration)፣ መለለዪ መምርሒታት ምጽራይ (feature encoding)፣ ከምኡውን ስትራተጂታት ምምሕያሽ ሞዴል (model optimization strategies) ተውህቦኻ ኣዕቢ። ዳታ (data) ናብ ተግባራዊ ምርዳእ ንምልዋጥን ኣብቲ ዓውዲ ሓድሽ ፈጠራ ንምምጻእን ምሳና ተጸምበሩ።
Apoia's Unique Features
Develop skills
Enhance your practical skills outlined below
ፍሉጥ ገምጋም ሞዴል (Master model evaluation): ብ Recall, F1-Score, ከምኡውን ብልክዕነት (Precision) ኣሃዝካ ኣመሓይሽ።
ብውጽኢታዊ መንገዲ ስራሕካ ጽሐፍ (Document effectively): ውሳኔታትካ ኣመኽንይን ውጽኢትካ ብንጹር ተርጉም።
ምዝባዕ ተንብ (Predict churn): ውሳኔታት ኣግራብ (Decision Trees)፣ ራንደም ፎረስትስ (Random Forests)፣ ከምኡውን ሎጂስቲክ ርገረሽን (Logistic Regression) ተጠቐም።
ዳታ ኣዳልው (Prepare data): መርመራ ዳህሳስ ፈጽምን ጉድለት ዘለዎ ዳታ ብትኽክል ኣወግድ።
ሞዴላት ኣመሓይሽ (Optimize models): ሜላታት ምጥርናፍ ስራሕ ኣብ ግብሪ ኣውዕልን ልዕል ዝበሉ መለክዒታት ኣሳልጥ።
Suggested summary
Workload: between 4 and 360 hours
Before starting, you can change chapters and workload.
- Choose which chapter to start with
- Add or remove chapters
- Increase or decrease the course workload
Examples of chapters you can add
You will be able to generate more chapters like the examples below
This is a free course, focused on personal and professional development. It is not equivalent to a technical, undergraduate, or postgraduate course, but offers practical and relevant knowledge for your professional journey.