Data Science | Advanced Certificate course

Data Science, data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data Science is a moderately new field in the field of technology. That is modifying the world of technology and our daily life,  If you don’t know that we use data science in many different ways. We use data science in our daily routine life to help us in our work, in our business, in our profession, in our field, and so on. It is everyplace and is the most critical thing for us to survive in this technical world.


 Data science is a newly arising field in the world of technology. It has been predicted that by 2025, there will be a demand for nearly 2.7 million data science jobs. And, according to IBM, the job market for data scientists will grow by 28% by 2020. This means that now is the time to get into this exciting and rapidly-growing field. One way to do this is by taking a data science course. This will give you the skills and knowledge you need to start a successful career in data science. The course will cover topics such as Introduction to Data Science, Python for Data Science, Machine Learning, Data Visualization, and Artificial Intelligence & Machine Learning. You will also learn how to use various tools and software for data analysis. 


After completing the course, you will be ready to start your new career in data science. Because in upcoming times this is one of the best sources for changing your career. You can make your career in these field Data Analyst, Data Engineer, Technical Specialist, Product Manager, Data Scientist, and Software Engineer. 


You can also want to learn about data science and want to make your career in this field and look for a beneficial course in data science. So you can get advice from Teletserve. For more details, you can 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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