Advanced Certificate Course In Data Science

Data science is the area of study that integrates domain expertise, programming skills, and knowledge of mathematics and statistics to extract expressive insights from data. And here you will learn these things Introduction to Data Science, Python for Data Science, Machine Learning, Data Visualization, and Artificial Intelligence & Machine Learning. It is a relatively new field and is growing rapidly. Data scientists are in high demand, as they are able to make sense of large amounts of data and find trends and patterns. 


Data Science can be used in many different fields, such as marketing, finance, healthcare, and manufacturing. Companies are always looking for ways to better understand their customers and target them more effectively. Data Science can help them do this by finding trends in customer behavior. Healthcare is another area where Data Science is having a major impact. Hospitals are using data to improve patient care and prevent medical errors. By analyzing patient data, hospitals can identify areas where there are opportunities for improvement. 

If you're interested in making a career in the Data Science filed, then you should definitely consider taking a course in it. There is a lot of demand for data scientists, and the skills you will learn will be very valuable in the job market. Data Science is a great career option for those who enjoy working with numbers. You will have the opportunity to work with the latest technologies and apply your skills to real-world problems. and to become an expert in Data Science. And for more details visit 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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