# Data Analytics Using Google CoLab : A course for Beginners

Data Analytics Using Google CoLab : A course for Beginners

Data analytics is a strategy-based science where raw data is analyzed to detect trends, answer questions, or draw conclusions from a large batch of data. Using various techniques, raw data is converted into a form that allows companies and organizations to analyze important metrics.

What you'll learn

• Problem solving skills related to data
• Detecting hidden pattern in the data
• Building Predictive models for different domains
• Basic concepts of Business Statistics and Machine Learning
• Time Series Forecasting
• Building Recommendation System
• Quiz on each section for evaluation

Description

In this course we have examples of analytics in a wide variety of industries, and we expect that students will learn how you can use data analytics in their career and become data analyst. One of the most important aspects of this course is that you, the student, are getting hands-on experience creating analytics data models. The course has four module first module give learner knowledge about python programming which include packages like Pandas, Numpy and Scipy are being taught in detail, second module introduces Business Statistics where students will get in depth knowledge of Descriptive Statistics, Inferential Statistics and Predictive Statistics along with their example in python i.e. how to implement all statistical modules in python, third module introduces to machine learning in which you will be introduced with Linear and Logistic Regression , Ordinary Least Squares, SVD and PCA for reducing dimensions of the data and the fourth module dedicated to implementation of learned ideas in projects where you were taught to work on data through four phases Data Discovery, Exploratory Data Analysis ,Model Building and result analysis. This is not an end you will going to have a free demo on "Building Movie Recommendation system from scratch" in Google CoLab.

View Best -- > Data Analysis with Pandas and Python

• Pandas provide extended data structures to hold different types of labeled and relational data. This makes python highly flexible and extremely useful for data cleaning and manipulation. Pandas is highly flexible and provides functions for performing operations like merging, reshaping, joining, and concatenating data.

Online Course CoupoNED based Analytics Education Company and aims at Bringing Together the analytics companies and interested Learners.