Data Science Course And Certification
What is Data Science?
Data Science is a study of various scientific processes, algorithms, methods and systems to extract information and gain deep insights from both structural and unstructural data.
People who study and work in the field of data science are called Data Scientists. They combine range of skills in collecting and analyzing data from various sources.
Data Scientists most times come from many different educational and work experience backgrounds.
1. Business Domain
2. Research Institute
3. Mathematics (includes statistics and probability)
4. Computer Science (e.g. software/data architecture and engineering)
5. Communication (both written and verbal)
As the world has come to an era of big data, the need for its storage also grew. This was the major challenges and concerns for the enterprise industries not until 2010.
The main focus was having the ability to building a framework and solutions to store data. Now when Hadoop and other frameworks have successfully found a solution to the problem of storage, the focus has now shifted to processing this data.
Data Science is the secret behind it here. All ideas which you can see in the Hollywood sci-fi movies can actually be changed into reality by Data Science.
Data Science can be themed as the future of Artificial Intelligence. Therefore, it is very important to learn and come to an understand of what Data Science is all about and how can it add value to your business.
What Does a Data Scientist Do?
A Data Scientist will take a deep view into the available data extracted from many sources and angles, then extrapolate these data and share the insights with analysts and organizations.
Some of the activities of Data Scientist are:
1. Identify the data-analytics problems that offer the greatest opportunities to the organization
2. Determine the correct data sets and variables
3. Collect large sets of structured and unstructured data from disparate sources
4. Clean and validate the data to ensure accuracy, completeness, and uniformity
5. Devise and apply models and algorithms to mine the stores of big data
6. Analyze the data to identify patterns and trends
7. Interprete the data to discover solutions and opportunities
8. Communicating findings to stakeholders such as analysts and organizations using visualizations and other presentation means.
What Does a Data Analyst Do?
Data Analyst will explain and interprete the extracted data in a clearer and consumable format.
Some of the methods of data presentations and analytics include:
Descriptive Analytics: evaluates and presents what has happened in the past in a descriptive and precisely clear format, such as monthly or yearly revenue, weekly sales, daily website traffic, daily page impressions, quarterly app purchases etc
Diagnostic Analytics: considers the reason for a past or current happenings by comparing descriptive data sets to identify dependencies and patterns per time.
Predictive Analytics: If you would like a model which will predict the chances of a specific event within the future, you would like to use predictive causal analytics. Here, you'll build a model which will perform predictive analytics on the payment history of the customer to predict if the longer term payments are going to be on time or not.
Prescriptive Analytics: If you would like a model that has the intelligence of taking its own decisions and therefore the ability to switch it with dynamic parameters, you certainly need prescriptive analytics for it.
Features and Benefits of Data Science
These are some of the numerous advantages of Data Science:
Data Science is in Demand
Data Science is Versatile
Data Science Makes Data Better
Data Science can Save Lives
Data Science Helps To Make Better Business Decisions
Helps to Ascertain Current and Future Trends
No More Boring Tasks
Insights from Data Science can help improve management operations and customer satisfaction among others.
Why Study Data Science
Reasons to learn Data Science
Data Science Makes Products Smarter
Data Science Offer Abundance of Positions
Data Scientists are Highly Prestigious
A Highly Paid Career
Enrich Your CV and Attract Better Jobs
Increase Your Earning Potential
Data Science Course Outline:
Data Science - Introduction
Data Science - Wrapping Your Head around Data Science
Data Science - Exploring Data Engineering Pipelines
Data Science - Applying Data-Driven Insights to Business
Data Science - Machine Learning: Learning from Data
Data Science - Math, Probability, and Statistical Modeling
Data Science - Using Clustering to Subdivide Data
Data Science - Modeling with Instances
Data Science - Building Models That Operate Internet-of-Things
Data Science - Following the Principles of Data Visualization
Data Science - Using D3.js for Data Visualization
Data Science - Web-Based Applications for Visualization
Data Science - Exploring Best Practices in Dashboard Design
Data Science - Making Maps from Spatial Data
Data Science - Using Python for Data Science
Data Science - Using Open Source R for Data Science
Data Science - Using SQL in Data Science
Data Science - Doing Data Science with Excel and Knime
Data Science - Data Science in Journalism: Nailing Down
Data Science - Delving into Environmental Data Science
Data Science - Data Science for Driving Growth in
Data Science - Using Data Science to Describe and Predict
Data Science - Phenomenal Resources for Open Data
Data Science - Free Data Science Tools and Applications
Data Science - Video Lectures
Data Science - Exams and Certification