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Computer Science Artificial Intelligence Course
Unlock the potential of Artificial Intelligence with our Computer Science Artificial Intelligence Course, tailored for technology professionals in India looking to upskill. Get hands-on with data preprocessing methods, become proficient in machine learning algorithms such as Support Vector Machines and Naive Bayes, and address spam detection problems. Learn to assess models using accuracy, precision, and recall, and improve them with practical strategies. Gain experience in model training, testing, and ethical data sourcing, preparing you to innovate in the Indian AI sector.
- Master evaluation metrics: Improve model accuracy and performance (especially relevant in the Indian context).
- Implement machine learning: Apply algorithms for effective spam detection and other relevant Indian use-cases.
- Optimise model training: Avoid overfitting and underfitting in AI models, crucial for real-world Indian data.
- Source ethical data: Identify and use open-source datasets responsibly, adhering to Indian data privacy norms.
- Preprocess data efficiently: Clean, tokenize, and convert text data, with a focus on Indian languages and dialects.
flexible workload of 4 to 360h
certificate recognized by MEC
What will I learn?
Unlock the potential of Artificial Intelligence with our Computer Science Artificial Intelligence Course, tailored for technology professionals in India looking to upskill. Get hands-on with data preprocessing methods, become proficient in machine learning algorithms such as Support Vector Machines and Naive Bayes, and address spam detection problems. Learn to assess models using accuracy, precision, and recall, and improve them with practical strategies. Gain experience in model training, testing, and ethical data sourcing, preparing you to innovate in the Indian AI sector.
Elevify advantages
Develop skills
- Master evaluation metrics: Improve model accuracy and performance (especially relevant in the Indian context).
- Implement machine learning: Apply algorithms for effective spam detection and other relevant Indian use-cases.
- Optimise model training: Avoid overfitting and underfitting in AI models, crucial for real-world Indian data.
- Source ethical data: Identify and use open-source datasets responsibly, adhering to Indian data privacy norms.
- Preprocess data efficiently: Clean, tokenize, and convert text data, with a focus on Indian languages and dialects.
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Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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