Data Science Advanced Certificate course in

Data science is not the future; it is the present! Data science is a newly emerging field in the world of technology. It is one of the sectors that have a huge demand for professionals. Data Science is the comprehensive study of data within an organization’s repository. It is a combination of data inference, algorithm development, and technology that work together to solve complex analytical problems. With the help of data science, organizations have procured meaningful insights from unstructured and raw data. 


The demand for skilled, knowledgeable, certified data scientists has grown recently. As a result, the number of people taking data science courses has increased significantly. Data scientists are now some of the highest-paid professionals. The meaning of data science is the comprehensive analysis of the processes used to extract large amounts of data to discern repetitive patterns. This aids in the organization and control of all the variable aspects of an organization, such as costs, competition, and the market. Data science is responsible for studying the origin of information, what it represents, and how it can be used beneficially in any project. 



You should join the Data Science course because India has a long scientific and technological advancement history. We're having great prosperity or rapid economic growth in IT and healthcare, and we've got a massive presence in many different areas. These sectors rely on data informative to make better decisions based on data that reveals consumer preferences and helps promote products to the correct audience. For more details, visit our site: 


https://www.talentserve.org/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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