# Data Science - End 2 End Beginners Course Part 1

#### Category: Tutorial

Posted on 2021-06-18, by perica123.

Description

Data Science - End 2 End Beginners Course Part 1

Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz

Language: English | Size: 11.0 GB | Duration: 22h 44m

Machine Learning & Data Analytics- Python, Pandas, Maths, Statistics, Probability, Regression, Classification,Clustering

What you'll learn

Part 1 is a Beginner's course that covers Machine Learning and Data Analytics

Objective is to teach students how to do an End-2-End data science project

From problem definition, data sourcing, wrangling, modelling, analyzing and visualizing to deploying and maintaining

Part 1 will cover all the basics required for building machine learning models - programming, analytics, maths, process, algorithms and deployment

It will provide full maths and logic details for all algorithms

Programming (python) and Data analytics (pandas)

Maths, Statistics and Probability basics required for understanding the different algorithms

Data Science Process - Problem, Wrangling, Algorithm Selection, Model Building , Visualization, Deployment

Data Wrangling

Build Machine Learning models - Supervised & Unsupervised algorithms using Regression, Classification & Clustering

How to Visualize and Evaluate models

Model Persistence and Deployment using joblib and flask, Deploying on AWS Cloud using S3 and Elastic Beanstalk, Using AWS Sagemaker

End 2 End Project - Building a RoboAdvisor - multi-asset portfolio using global assets and macroeconomic data

Detailed python code and data is provided to explain all concepts and algorithms

Use popular libraries like scikit-learn, xgboost, numpy, matplotlib, seaborn, joblib, flask, etc

Description

This is a Beginner's course that covers basic Machine Learning and Data Analytics concepts

The Objective of this course is to teach students how to do an End-2-End data science project

From Problem definition, data sourcing, wrangling and modelling

To analyzing, visualizing and deploying & maintaining the models

It will cover the main principles/tools that are required for data science

This course is for anyone interested in learning data science - analyst, programmer, non-technical professional, student, etc

Having seen available data science courses and books, we feel there is a lack of an End 2 End approach

Quite often you learn the different algorithms but don't get a holistic view, especially around the process and deployment

Also, either too much or limited mathematical details are provided for different algorithms

The course will cover all the basics in programming, maths, statistics and probability required for building machine learning models

Throughout the course detailed lectures covering the maths and logic of the algorithms, python code e x a mples and online resources are provided to support the learning process

Students will learn how to build and deploy machine learning models using tools and libraries like anaconda, spyder, python, pandas, numpy, scikit-learn, xgboost, matplotlib, seaborn, joblib, flask, AWS Cloud S3, Elastic Beanstalk and Sagemaker

More details are available on our website - datawisdomx

Course material including python code and data is available in github repository - datawisdomx, DataScienceCourse

Who this course is for:

This course is for anyone interested in learning data science

From beginners to intermediate level users

Analyst, programmer, non-technical professional, student, etc

Data Analysts, Machine Learning engineers, Data Engineers, Business Analysts who want to become Data Scientists

Homepage

https://anonymz.com/?https://www.udemy.com/course/datascience-e2e-beginnerscourse-machinelearning-dataanalytics/

https://nitro.download/view/91C0E1C56694231/Data_Science_%E2%80%93_End_2_End_Beginners_Course_Part_1.part01.rar

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https://rapidgator.net/file/c51cd61bbd1a2a571098fc39a064ed30/Data_Science_-_End_2_End_Beginners_Course_Part_1.part01.rar.html

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