Data Science as I always define is not about writing a very complicated script or code.
Data Science is making use of data to generate insights which provides an impact and value for a company. Value could be in the form of a products that can offer by the company to their stakeholders in exchange of a revenue, it could be in the form of a products that will help improve Business processes. It could be in the form of a product recommendations for the company.
Data is an essential driver for growth and transformation initiative of every organizations; thus, it is a must to build and develop framework and infrastructure to organize and manage data. To effectively handle and manage Big Data, they will be needing tools such as MapReduce, Hadoop, Spark, and many others. One must need someone who understand the engineering and architecture of Big Data, thus the rise of Data Architect and Data Engineer.
Once the Architecture and Engineering of Big Data was established, Data Scientist can now make use of data to generate insights for the company and their stakeholders. Building a scalable dashboard for the company, building a data-driven model, attrition model for Human Resources, Improve Business Processes, fraud detection algorithm, Automation, Build and Develop Artificial Intelligence Applications, Build a Machine Learning Algorithms, Virtual Reality, Internet of things, and many other products and services are only few among the abilities and competencies of a Data Scientist.
To serve their purpose, they will be needing programming and analytics tools such as R, Python, SAS, and many others. They will also need some Visualization Tools such as Tableau, D3, Sisense, QlikView, etc.
The journal of Data Science described this domain of skills and expertise as almost everything which encapsulate skills, knowledge and competencies in Statistics/ Data Mining and Data Wrangling. Data Scientist must also exhibit skills in Computer Science and have a high level of Business Managements.
With this, I am very excited to invite everyone to take and enroll in this comprehensive course on Data Science. This course will cover the three main domain of knowledge and competencies needed to become a good data scientist as it encapsulate skills in Statistics, Data Mining, Data Wrangling, Exploratory Data Analysis, Different Distribution of Data, Multivariate Statistics and many other. Also included in this course is the basics of Computer Programming Language such as Python. It also includes some of the most used Algorithms in the areas of Data Science. There are also practical exercises to work on using Python programming.
(NOTE: This course is completely patterned with Certificate Courses, but you don't need to pay for a higher rate. Usually, certificate courses requires a students to pay for a higher rate in exchange of a Certificate.
The coverage of this course is similar and patterned with certificate courses. My priority is the learning that you can earned and get from this course. The only difference is the certificate.
If you want to have a certificate, I am happy to connect you to the university where I am also offering this course. This is an online schooling)