Best Data Science Course in Mumbai

What is data science? Data science is the process of extracting knowledge from data. It involves the use of scientific methods, algorithms, and tools to collect, process, and analyze data. Data science can be used to find trends and patterns, make predictions, and take actionable insights from data. Data science is a multidisciplinary field that combines statistics, computer science, and domain expertise to solve problems with data. 

Data scientists use their skills in programming, mathematics, and statistics to wrangle data, build models, and make insights. The goal of data science is to turn data into insights and actionable plans. Data scientists work with businesses to help them make better decisions, drive growth, and improve operations. They use their skills in statistics, computer science, and domain expertise to understand problems and find solutions.


As the world becomes more and more digitized, the demand for data scientists is only going to grow. If you're looking to start a career in this exciting field, our Data Science course is the perfect place to start. In this course, you'll learn the basics of working with data, from acquiring and cleaning it, to performing basic analysis and visualizations. You'll also get an introduction to machine learning, and will learn how to build and evaluate predictive models. By the end of the course, you'll be able to answer important business questions using data, and will have the skillset you need to start a successful career as a data scientist. So why wait? Enroll in our Data Science course today. 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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