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Data Science SEMINAR

Course Duration: Minimum 10 Days
Curriculum Delivery: Online / Offline
Timings & Schedules: Flexible time shift as per the convenience of candidates
Certification Authority: AIT Issued Seminar Completion Certificate
Seminar Index: Seminar Paper Research, Seminar Presentation Training, Documentation, Demo viva Section, PPT Presentation

About The Seminar

ATEES Industrial Training seminar paper involves everything that one needs to be successful in their respective career. The courses are designed to help candidates comprehend the topic and incorporate apt skills in their professional writing. We welcome questions from our candidates on how we can help them with the seminar preparation. In addition, our support team will guide one with seminar topics including quality discussion on the logical idea and technologies involved. The seminar paper is presented in four major sections: Introduction; Background; Analysis; and Conclusion. Each sub-sections will be researched and examined in detail in the subsequent pages.

Data science is a discipline that integrates mathematics, statistics, specialised programming, sophisticated analytics, artificial intelligence (AI), machine learning, and specialised subject matter expertise to find useful information buried in data. Decision-making and strategic planning can be influenced by these findings. You will receive a general understanding of the following topics: Why Data Science, Data Science using Python, Components, Functions, and File Structure in Data Science. You can see how each component interacts with the section as a whole by looking at a variety of presentations that make up the section. Following the definition of each component of a topic, the content is cross-checked using a variety of technology-based research methods.

  • Why was created?
  • Features
  • Conclusion

No. Seminar Topics
1 Rainfall Forecasting Using Machine Learning Approaches (ML+Python+DB Sqlite)
2 Machine learning application in wine quality prediction (ML+Python+DB Sqlite)
3 Skeleton Based Abnormal Pedestrian Behaviour Recognition Using Spatio-Temporal Convolution and Attention-Based LSTM(ML+Python+DB Sqlite)
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