Advanced Certificate Course In Data Science With Placement

Data science is a relatively new field that deals with extracting meaning from data using scientific methods. Data science courses teach students how to use statistical methods and software to analyze data sets, extract insights, and solve real-world problems. The benefits of data science courses include learning cutting-edge skills that are in high demand by employers, developing analytical and problem-solving abilities, and gaining a better understanding of the world around us.

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. It is a relatively new field that has emerged from the intersection of statistics, computer science, and business. The Data Science course at our university provides students with the skills and knowledge necessary to become data scientists. The course covers a wide range of topics, including data mining, machine learning, statistical modeling, data visualization, and more. 

The benefits of taking this course are many; some of the most notable include: -Learning how to effectively analyze and interpret data -Gaining an understanding of how businesses use data to make decisions -Developing skills in critical thinking and problem solving -Becoming proficient in using industry-standard tools and techniques Overall, the Data Science course provides students with a solid foundation on which to build their careers as data scientists. With the ever-increasing demand for skilled data professionals, this course is an excellent choice for those looking to enter this exciting and growing field. For more details, you can check our site: https://www.talentserve.org/course-datascience

 COURSE CONTENT


  • Introduction to Python

  • Basic Steps

  • NUMPY

  • Data Visualization

  • Pandas

  • Exceptions and Errors

  • Introduction to Artificial Intelligence and Machine Learning

  • Data Wrangling and Manipulation

  • Supervised Learning

  • Supervised Learning-Classification

  • Unsupervised learning

  • Machine Learning Pipeline Building

  • Decision Tree Analysis and Ensemble Learning

  • AI and Deep learning introduction

  • Artificial Neural Network

  • Deep Neural Network & Tools

  • Deep Neural Net optimization, tuning, interpretability

  • Convolutional Neural Net

  • Recurrent Neural Networks

  • Overfit and underfit

  • Transfer Learning

  • Working with Generative Adversarial Networks

  • Pytorch

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