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Statistics for Data Science and Business Analysis [PDF]

Statistics you need in the office: Descriptive & Inferential statistics, Hypothesis testing, Regression analysis

What you’ll learn

Statistics for Data Science and Business Analysis Course Site

  • Understand the fundamentals of statistics
  • Learn how to work with different types of data
  • How to plot different types of data
  • Calculate the measures of central tendency, asymmetry, and variability
  • Calculate correlation and covariance
  • Distinguish and work with different types of distributions
  • Estimate confidence intervals
  • Perform hypothesis testing
  • Make data-driven decisions
  • Understand the mechanics of regression analysis
  • Carry out regression analysis
  • Use and understand dummy variables
  • Understand the concepts needed for data science even with Python and R!

Requirements

  • Absolutely no experience is required. We will start from the basics and gradually build up your knowledge. Everything is in the course.
  • A willingness to learn and practice

Description

Is statistics a driving force in the industry you want to enter? Do you want to work as a Marketing Analyst, a Business Intelligence Analyst, a Data Analyst, or a Data Scientist?
Well then, you’ve come to the right place!

This is where you start. And it is the perfect beginning!

In no time, you will acquire the fundamental skills that will enable you to understand complicated statistical analysis directly applicable to real-life situations. We have created a course that is:

  • Easy to understand
  • Comprehensive
  • Practical
  • To the point
  • Packed with plenty of exercises and resources
  • Data-driven
  • Introduces you to the statistical scientific lingo
  • Teaches you about data visualization
  • Shows you the main pillars of quant research

Modern software packages and programming languages are automating most of these activities, but this course gives you something more valuable – critical thinking abilities. Computers and programming languages are like ships at sea. They are fine vessels that will carry you to the desired destination, but it is up to you, the aspiring data scientist or BI analyst, to navigate and point them in the right direction.

Teaching is our passion

We worked hard for over four months to create the best possible Statistics course which would deliver the most value to you. We want you to succeed, which is why the course aims to be as engaging as possible. High-quality animations, superb course materials, quiz questions, handouts, and course notes, as well as a glossary with all new terms you will learn, are just some of the perks you will get by subscribing. Statistics for Data Science and Business Analysis Course Site

What makes this course different from the rest of the Statistics courses out there?

  • High-quality production – HD video and animations (This isn’t a collection of boring lectures!)
  • Knowledgeable instructor (An adept mathematician and statistician who has competed at an international level)
  • Complete training – we will cover all major statistical topics and skills you need to become a marketing analyst, a business intelligence analyst, a data analyst, or a data scientist
  • Extensive Case Studies that will help you reinforce everything you’ve learned
  • Excellent support – if you don’t understand a concept or you simply want to drop us a line, you’ll receive an answer within 1 business day
  • Dynamic – we don’t want to waste your time! The instructor sets a very good pace throughout the whole course

Why do you need these skills?

  1. Salary/Income – careers in the field of data science are some of the most popular in the corporate world today.
  2. Promotions – If you understand Statistics well, you will be able to back up your business ideas with quantitative evidence, which is an easy path to career growth
  3. Secure Future – as we said, the demand for people who understand numbers and data, and can interpret it, is growing exponentially;
  4. Growth – this isn’t a boring job. Every day, you will face different challenges that will test your existing skills and require you to learn something new

Please bear in mind that the course comes with Udemy’s 30-day unconditional money-back guarantee. And why not give such a guarantee? We are certain this course will provide a ton of value for you.

Who this course is for:

  • People who want a career in Data Science
  • People who want a career in Business Intelligence
  • Business analysts
  • Business executives
  • Individuals who are passionate about numbers and quant analysis
  • People who want to start learning statistics
  • People who want to learn the fundamentals of statistics

Updated 2/2020

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Business Managment Data Science

Big Data and Hadoop for Beginners – with Hands-on

Everything you need to know about Big Data and Learn Hadoop, HDFS, MapReduce, Hive & Pig by designing Data Pipeline.

What you’ll learn

Big Data and Hadoop for Beginners – with Hands-on Course Site

  • Understand different technology trends, salary trends, Big Data market and different job roles in Big Data
  • Learn what is Hadoop is for, and how it works
  • Understand the complex architectures of Hadoop and its component
  • Hadoop installation on your machine
  • High-quality documents
  • Demos: Running HDFS commands, Hive queries, Pig queries
  • Sample data sets and scripts (HDFS commands, Hive sample queries, Pig sample queries, Data Pipeline sample queries)
  • Start writing your codes in Hive and Pig to process huge volumes of data
  • Design your data pipeline using Pig and Hive
  • Understand modern data architecture: Data Lake
  • Practice with Big Data sets

Requirements

  • Basics knowledge of SQL and RDBMS would be a plus
  • Machine- Mac or Linux/Unix or Windows

Description

The main objective of this course is to help you understand Complex Architectures of Hadoop and its components, guide you in the right direction to start with, and quickly start working with Hadoop and its components.It covers everything that you need as a Big Data Beginner. Learn about the Big Data market, different job roles, technology trends, history of Hadoop, HDFS, Hadoop Ecosystem, Hive, and Pig. In this course, we will see how as a beginner one should start with Hadoop. This course comes with a lot of hands-on examples that will help you learn Hadoop quickly.

The course has 6 sections, and focuses on the following topics:

Big Data at a Glance: Learn about Big Data and different job roles required in the Big Data market. Know big data salary trends around the globe. Learn about the hottest technologies and their trends in the market.

Getting Started with Hadoop: Understand Hadoop and its complex architecture. Learn  Hadoop Ecosystem with simple examples. Know different versions of Hadoop (Hadoop 1.x vs Hadoop 2.x), different Hadoop Vendors in the market and Hadoop on Cloud. Understand how Hadoop uses the ELT approach. Learn to install Hadoop on your machine. We will see running HDFS commands from the command line to manage HDFS.

Getting Started with Hive: Understand what kind of problem Hive solves in Big Data. Learn its architectural design and working mechanism. Know data models in Hive, different file formats supported by Hive, Hive queries, etc. We will see running queries in Hive.

Getting Started with Pig: Understand how Pig solves problems in Big Data. Learn its architectural design and working mechanism. Understand how Pig Latin works in Pig. You will understand the differences between SQL and Pig Latin. Demos on running different queries in Pig.

Use Cases: Real-life applications of Hadoop are important to better understand Hadoop and its components, hence we will be learning by designing a sample Data Pipeline in Hadoop to process big data. Also, understand how companies are adopting modern data architecture i.e. Data Lake in their data infrastructure.

Practice: Practice with huge Data Sets. Learn Design and Optimization Techniques by designing Data Models, Data Pipelines by using real-life applications’ data sets.

Who this course is for:

  • This course assumes everyone as a beginner and teaches all fundamentals of Big Data, Hadoop and its complex architecture.
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Business Managment Data Science Udemy Courses

The Data Science Course 2020: Complete Data Science Bootcamp

Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What Will I Learn?

  • The course provides the entire toolbox you need to become a data scientist
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Impress interviewers by showing an understanding of the data science field
  • Learn how to pre-process data
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Start coding in Python and learn how to use it for statistical analysis
  • Perform linear and logistic regressions in Python
  • Carry out cluster and factor analysis
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Apply your skills to real-life business cases
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Unfold the power of deep neural networks
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations.

Requirements

  • No prior experience is required. We will start from the very basics
  • You’ll need to install Anaconda. We will show you how to do that step by step
  • Microsoft Excel 2003, 2010, 2013, 2016, or 365

Description

The Problem

Data scientist is one of the best suited professions to thrive in this century. Digital. Programming-oriented. Analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace.

However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist.

And how can you do that?

Universities have been slow at creating specialized data science programs. (not to mention that the ones that exist are very expensive and time consuming)

Most online courses focus on a specific topic and it is difficult to understand how the skill they teach fit in the complete picture

The Solution

Data science is a multidisciplinary field. It encompasses a wide range of topics.

  • Understanding of the data science field and the type of analysis carried out
  • Mathematics
  • Statistics
  • Python
  • Applying advanced statistical techniques in Python
  • Data Visualization
  • Machine Learning
  • Deep Learning

Each of these topics builds on the previous ones. And you risk getting lost along the way if you don’t acquire these skills in the right order. For example, one would struggle in the application of Machine Learning techniques before understanding the underlying Mathematics. Or, it can be overwhelming to study regression analysis in Python before knowing what a regression is.

So, in an effort to create the most effective, time-efficient, and structured data science training available online, we created The Data Science Course 2018.

We believe this is the first training program that solves the biggest challenge to entering the data science field – having all the necessary resources in one place.

Moreover, our focus is to teach topics that flow smoothly and complement each other. The course teaches you everything you need to know to become a data scientist at a fraction of the cost of traditional programs (not to mention the amount of time you will save).

The Skills

1. Intro to Data and Data Science

Big data, business intelligence, business analytics, machine learning and artificial intelligence. We know these buzzwords belong in the field of data science but what do they all mean? As a candidate data scientist, you must understand the ins and outs of each of these areas and recognise the appropriate approach to solving a problem. This ‘Intro to data and data science’ will give you a comprehensive look at all these buzzwords and where they fit in the realm of data science.

Why learn it?

2. Mathematics

Learning the tools is the first step to doing data science. You must first see the big picture to then examine the parts in detail.

We take a detailed look specifically at calculus and linear algebra as they are the subfields data science relies on.

Why learn it?

Calculus and linear algebra are essential for programming in data science. If you want to understand advanced machine learning algorithms, then you need these skills in your arsenal.

3. Statistics

You need to think like a scientist before you can become a scientist. Statistics trains your mind to frame problems as hypotheses and gives you techniques to test these hypotheses, just like a scientist.

Why learn it?

This course doesn’t just give you the tools you need but teaches you how to use them. Statistics trains you to think like a scientist.

4. Python

Python is a relatively new programming language and, unlike R, it is a general-purpose programming language. You can do anything with it! Web applications, computer games and data science are among many of its capabilities. That’s why, in a short space of time, it has managed to disrupt many disciplines. Extremely powerful libraries have been developed to enable data manipulation, transformation, and visualisation. Where Python really shines however, is when it deals with machine and deep learning.

Why learn it?

When it comes to developing, implementing, and deploying machine learning models through powerful frameworks such as scikit-learn, TensorFlow, etc, Python is a must have programming language.

5. Tableau

Data scientists don’t just need to deal with data and solve data driven problems. They also need to convince company executives of the right decisions to make. These executives may not be well versed in data science, so the data scientist must but be able to present and visualise the data’s story in a way they will understand. That’s where Tableau comes in – and we will help you become an expert story teller using the leading visualisation software in business intelligence and data science.

Why learn it?

A data scientist relies on business intelligence tools like Tableau to communicate complex results to non-technical decision makers.

6. Advanced Statistics

Regressions, clustering, and factor analysis are all disciplines that were invented before machine learning. However, now these statistical methods are all performed through machine learning to provide predictions with unparalleled accuracy. This section will look at these techniques in detail.

Why learn it?

Data science is all about predictive modelling and you can become an expert in these methods through this ‘advance statistics’ section.

7. Machine Learning

The final part of the program and what every section has been leading up to is deep learning. Being able to employ machine and deep learning in their work is what often separates a data scientist from a data analyst. This section covers all common machine learning techniques and deep learning methods with TensorFlow.

Why learn it?

Machine learning is everywhere. Companies like Facebook, Google, and Amazon have been using machines that can learn on their own for years. Now is the time for you to control the machines.

***What you get***

  • A $1250 data science training program
  • Active Q&A support
  • All the knowledge to get hired as a data scientist
  • A community of data science learners
  • A certificate of completion
  • Access to future updates
  • Solve real-life business case that will get you the job

You will become a data scientist from scratch

We are happy to offer an unconditional 30-day money back in full guarantee. No risk for you. The content of the course is excellent, and this is a no-brainer for us, as we are certain you will love it.

Why wait? Every day is a missed opportunity.

Click the “Buy Now” button and become a part of our data scientist program today.Who is the target audience?

  • You should take this course if you want to become a Data Scientist or if you want to learn about the field
  • This course is for you if you want a great career
  • The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills

Size: 14.07 GB

Categories
Business Managment Data Science Python Courses

PYTHON FOR DATA SCIENCE AND MACHINE LEARNING BOOTCAMP

Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more!

  • Use Python for Data Science and Machine Learning
  • Use Spark for Big Data Analysis
  • Implement Machine Learning Algorithms
  • To use NumPy for Numerical Data
  • Learn to use Pandas for Data Analysis
  • Learn to use Matplotlib for Python Plotting
  • To use Seaborn for statistical plots
  • Use Plotly for interactive dynamic visualizations
  • Use SciKit-Learn for Machine Learning Tasks
  • K-Means Clustering
  • Logistic Regression
  • Linear Regression
  • Random Forest and Decision Trees
  • Natural Language Processing and Spam Filters
  • Neural Networks
  • Support Vector Machines

Requirements

  • Some programming experience
  • Admin permissions to download files

Description

Are you ready to start your path to becoming a Data Scientist!

This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!

Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world’s most interesting problems!

This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!

This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy!

We’ll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Here a just a few of the topics we will be learning:

  • Programming with Python
  • NumPy with Python
  • Using pandas Data Frames to solve complex tasks
  • Use pandas to handle Excel Files
  • Web scraping with python
  • Connect Python to SQL
  • Use matplotlib and seaborn for data visualizations
  • Use plotly for interactive visualizations
  • Machine Learning with SciKit Learn, including:
  • Linear Regression
  • K Nearest Neighbors
  • K Means Clustering
  • Decision Trees
  • Random Forests
  • Natural Language Processing
  • Neural Nets and Deep Learning
  • Support Vector Machines
  • and much, much more!

Enroll in the course and become a data scientist today!Who is the target audience?

  • This course is meant for people with at least some programming experience

Size: 3.67G

If you are facing any problem regarding downloading course then do refer Complete Downloading Guide & Torrent Deadline.