Course details
Learn Data Science & Machine Learningby doing! Hands On Experience
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 complete beginners with no programming experience or experienced developers looking to make the jump to Data Science!
This course is for those :
1.Who wants to be Data Scientist
2. Who are working as analyst / softwaredeveloper but wants to beData Scientist
What is Data Science ?
Data science is usedto extract patterns or insights fromdatato predict future or to understand customer behavior and so on.
Data science is a "concept to unify statistics, data analysis and their related methods" in order to "understand and analyze actual phenomena" with data
Mining large amounts of structured and unstructured data to identify patterns can help an organization to reduce costs, increase efficiencies, recognize new market opportunities and increase the organization's competitive advantage.
Some Data Science and machine learning Applications
- Netflix uses data science & machine learningtominemovie viewing patterns to understand what drives user interest, and uses that to make decisions on which Netflix original series to produce.
- Companies like Flipkart and Amazon uses data science and machine learning to understand the customer shopping behavior to dobetter recommendations.
- Gmail's spam filter uses data science (machine learning algorithm) to processincoming mail and determines if a message is junk or not..
- Proctor & Gamble utilizes data science (machine learning)models to more clearly understand future demand, which help plan for production levels more optimally.
Why ProgrammingWon't Work in some Cases??
Have you ever thought of the scenario where all the cars will be moving without a driver that means something like automated machines say for example automatic washing machine.
But there is a difference.
1. For automatic washing machine,we can write programs for the washing machine functionality.
2. For automated cars without drivers in high traffic.Just imagine ,how complex and dangerous it will be when someone starts coding /programming for such functionalities.For cars to automate we would require something which is called "Machine Learning"
In this course, we are firstgoing to first discuss
- Data Structures,etc. in R like :
1. Vectors
2. Matrices
3. Data Frames
4. Factors
5. Numerical/Categorical Variables
6. List
7. How to convert matrix into data frame
- Programming in R
- Data Visualization
- Then implementation/working of machine learningmodels like
1. Linear Regression
2. Decision Tree
3. Random Forest
4.Neural Networks
5. Deep learning
6. H2o framework
7. Cross validation /How to avoidOver fitting
8. Dimensionality Reduction Techniques
All the materials for this data science & machine learning course are FREE. You can download and installR, with simple commands onWindows, Linux, or Mac.
This course focuses on "how to build and understand", not just "how to use".It's not about "remembering facts", it's about"seeing for yourself" via experimentation. It will teach you how to visualize what's happening in the model internally.
Enroll in the course and become a data scientist today!
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