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Updated in [February 21st, 2023]

What does this course tell?
(Please note that the following overview content is from the original platform)


Tutorial 1- FAQ Chatbot Using RASA NLU.
Tutorial 2- FAQ Chatbot Using RASA NLU- Chatbot Introduction.
Tutorial 3- FAQ Chatbot Using RASA NLU- Introduction To RASA.
Tutorial 4- FAQ Chatbot Using RASA NLU- FAQ Problem Statement.
Tutorial 5- FAQ Chatbot Using RASA NLU- FAQ Chatbot Implementation.
Tutorial 6- FAQ Chatbot Using RASA NLU- Telegram Integration.
Tutorial 7- FAQ Chatbot Using RASA NLU- Conclusion and Further Work.


We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
1. You can learn how to build a FAQ chatbot using RASA NLU. This course will provide you with a comprehensive introduction to RASA NLU, including how to create a problem statement, implement a chatbot, and integrate it with Telegram. You will also gain an understanding of the fundamentals of natural language processing and how to use it to create a chatbot.

2. You can gain an understanding of natural language processing and how to use it to create a chatbot. This course will provide you with an overview of the fundamentals of natural language processing and how to use it to create a chatbot. You will also learn how to create a problem statement, implement a chatbot, and integrate it with Telegram.

3. You can learn how to create a problem statement and implement a chatbot. This course will provide you with an overview of the fundamentals of natural language processing and how to use it to create a chatbot. You will also learn how to create a problem statement, implement a chatbot, and integrate it with Telegram.

4. You can learn how to integrate a chatbot with Telegram. This course will provide you with an overview of the fundamentals of natural language processing and how to use it to create a chatbot. You will also learn how to create a problem statement, implement a chatbot, and integrate it with Telegram.

5. You can gain an understanding of the fundamentals of natural language processing. This course will provide you with an overview of the fundamentals of natural language processing and how to use it to create a chatbot. You will also learn how to create a problem statement, implement a chatbot, and integrate it with Telegram.

[Applications]
After completing this course, participants can apply the knowledge gained to create their own FAQ chatbot using RASA NLU. They can also use the Telegram integration to deploy their chatbot on the Telegram platform. Additionally, they can explore further work such as adding more features to their chatbot or integrating it with other platforms.

[Career Paths]
1. Natural Language Processing (NLP) Engineer: Natural Language Processing Engineers are responsible for developing and implementing algorithms and models to process and interpret natural language. They must have a strong understanding of machine learning, deep learning, and natural language processing techniques. This job is becoming increasingly important as more companies are looking to use natural language processing to improve customer service, automate tasks, and create more efficient systems.

2. Chatbot Developer: Chatbot Developers are responsible for creating and maintaining chatbot applications. They must have a strong understanding of natural language processing, machine learning, and artificial intelligence. They must also be able to design and develop user interfaces and integrate chatbot applications with existing systems. This job is becoming increasingly important as more companies are looking to use chatbots to improve customer service, automate tasks, and create more efficient systems.

3. AI/ML Engineer: AI/ML Engineers are responsible for developing and implementing algorithms and models to process and interpret data. They must have a strong understanding of machine learning, deep learning, and artificial intelligence techniques. This job is becoming increasingly important as more companies are looking to use AI/ML to improve customer service, automate tasks, and create more efficient systems.

4. Data Scientist: Data Scientists are responsible for analyzing and interpreting data to uncover insights and trends. They must have a strong understanding of statistics, machine learning, and data visualization techniques. This job is becoming increasingly important as more companies are looking to use data science to improve customer service, automate tasks, and create more efficient systems.