Learn entire Probability and Statistics, Python, Data Gathering and Cleaning, Machine Learning and Data Visualization

**This course includes:**- 4.5 hours on-demand video
- 6 articles
- 11 downloadable resources
- 1 practice test
- Full lifetime access
- Access on mobile and TV
- Certificate of completion

**What you'll learn**

- Become a well round Data Scientist
- Python Programming for Data Science
- Complete working flow of Data Science project
- Role of Data Scientist in Today's World
- How to apply Probability concepts to Solve real life problems
- Collecting Data from API (Application Programming Interface)
- Collecting Data from JSON
- Collecting Data from Local file, and CSV and Excel
- Learn different techniques to clean the data
- Probability for Data Science - Probability definition, Random Variables, Probability Distribution, Bayes' Theorem
- Discrete and Continuous Probability Distribution
- Basic Statistical Concepts for Data Science
- Learn about Collections in Python
- What is Machine Learning and its types
- Machine Learning Models - Simple and Multiple Linear Regression, Advance Linear Regression, Decision Tree, SVM, K-means Clustering
- Supervised and Unsupervised machine learning models
- Learn to use the popular library Scikit-learn in your projects
- Learn to perform Classification and Regression modelling
- Probability Distributions - Binomial Distribution, Normal Distribution and Poisson Distribution
- Statistical Concepts - Mean, Mode, Median and Standard Deviation
- Data Visualization

**Description**

If I will tell the scope and future of data science in the World is very high and Data Scientist is the most in-demand profession today, I am sure you won’t trust. What if a great leader says so. According to Tim Berners Lee, the inventor of the World Wide Web–

"Data is a Precious Thing and will Last Longer than the Systems themselves."

Also, Vinod Khosla, an American Billionaire Businessman and Co-founder of Sun Microsystems declared –

"In the next 10 years, Data Science and Software will do more for Medicines than all of the Biological Sciences together."

By the above two statements, it is clear that data proliferation will never end and because of that, the use of data related technologies like Data Science and Big Data is increasing day by day. 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!

Data science is used by “computing professionals who have the skills for collecting, shaping, storing, managing, and analyzing data [as an] important resource for organizations to allow for data-driven decision making.” Almost every interaction with technology includes data—your Amazon purchases, Facebook feed, Netflix recommendations, and even the facial recognition required to sign in to your phone.

Amazon is a prime example of just how helpful data collection can be for the average shopper. Amazon’s data sets remember what you’ve purchased, what you’ve paid, and what you’ve searched. This allows Amazon to customize its subsequent homepage views to fit your needs. For example, if you search camping gear, baby items, and groceries, Amazon will not spam you with ads or product recommendations for geriatric vitamins. Instead, you are going to see items that may actually benefit you, such as a compact camping high chair for infants.

WHY SHOULD I ENROLL FOR THIS COURSE?

In this course, we will start right from the basics like what is Data Science? Most of the people are often confused when they are asked - “WHAT IS DATA SCIENCE?” The most common reply is - “UM, MACHINE LEARNING. ” Well, Machine Learning is a part of data science domain but it doesn’t mean that machine learning is the synonym of data science.

So in this course, you will learn all the basic concepts related to data science in a step by step approach. 1st you will learn about Probability and statistics. Probability and statistics help to bring logic to a world replete with randomness and uncertainty. This course will give you tools needed to understand data science, engineering, and finance. You will learn not only how to solve challenging technical problems, but also how you can apply those solutions in everyday life.

Then you will learn what is programming and programming language for data science using Python. You will learn the basics of python language, Collections, keywords and variables, control flow statements and functions in python. After that, you will learn the most important task of data scientist which is collecting data from different sources and clean and prepare that data for analysis. You will learn how to gather data from local files, CSV and Excel, JSON file and API. But when you collect any it will be definitely in a messy format. So you will also learn how to clean that data in a simple way so that you can spend less time on cleaning data and more time on exploring and modeling data. And in the end, you will learn different machine learning models from which you can train your data and find insights from it.

In this course, you will learn the entire data science project timeline in a step by step manner. And with a simple explanation language and use of real-life examples for better explanation purposes will help you to understand the important concepts in a simple and relatable manner.

**Also See : Data Science, Machine Learning, Data Analysis, Python & R**