Advance Certificate Course In Data Science | Learn With Talentserve

There are a number of data science courses available that can help you learn the skills you need to pursue a career in this exciting field. Talentserve offers a comprehensive data science course that covers everything from the basics of data analytics to more advanced topics like machine learning and artificial intelligence. The course is designed to give you the skills you need to succeed in a data science career, and the talented team of instructors will ensure you get the most out of your learning experience. With their help, you'll be able to build a strong foundation in data science and be well on your way to an exciting new career. 


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, similar to data mining. Data science is a "concept to unify statistics, data analysis, machine learning, and their related methods" in order to "understand and analyze actual phenomena" with data. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, computer science, and information science. 

Data Science Central describes five core skills required for a successful career in data science: statistics & mathematics; hacking skills; domain expertise; strong communication abilities; and business strategy. A recent study has found that there are currently more than four times as many job postings for data scientists as there are qualified applicants willing and able to fill those roles. So if you're thinking of pursuing a career in data science, then join our course 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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