Introduction
Data science is a field of study that works with large amounts of data and uses cutting-edge tools and techniques to uncover hidden patterns, extract useful data, and make business choices. To create prediction models, data scientists utilize complex machine learning algorithms.
What you will Learn?
In this course, you will learn about the basics of data science, python programming, R programming, SQL, fundamentals of statistics. You will learn how to preprocess data and exploratory data analysis. Learn to create machine learning and deep learning models to predict the unknown and evaluate your model. You will also learn how to use Time series analysis , Text Mining and NL. Then in the end you build the project for hands-on practice.
Prerequisite: An eagerness to learn and an open mind.
| Title | Duration |
|---|---|
| Beginner - Introduction to Data Science | 2 Hrs |
| Beginner - Python for Data Science | 15 Hrs |
| Beginner - Basics of Statistics | 4 Hrs |
| Beginner - Data Analysis using Python | 15 Hrs |
| Beginner - Data Visualization using Python | 15 Hrs |
| Beginner - Machine learning with Python | 30 Hrs |
| Intermediate - Data Analysis using SQL | 30 Hrs |
| Intermediate - Data Visualization using Tableau | 20 Hrs |
| Intermediate - Data Analysis using R Programming | 30 Hrs |
| Advanced - Working with Keras and TensorFlow | 40 Hrs |
| Advanced - Time Series Data Analysis | 40 Hrs |
| Advanced - Text Mining and Natural Language Processing (NLP) | 40 Hrs |
| Advanced - Artificial Neural Network | 40 Hrs |
| Capstone Project | 40 Hrs |