HRDF HRD Corp Claimable Data Science Analytics Training
100% HRDF / HRC Corp Claimable Data Science Analytics Training
10-12 July 2023 – 9am till 5pm
Outline of a Course in Data Science and Analytics
The abilities necessary to become a successful Data Analyst can be developed through participation in this three-day workshop. You will be able to successfully study various forms of data and transform it into a valuable sources of information if you take this course. You will also have the opportunity to gain knowledge of a variety of ideas, such as digital, technological, and analytical methodologies.
During the course of this certification, the following subjects will be covered:
- A Brief Introduction to the Field of Data Science
- Understanding Data Wrangling
- Data Analysis
- Data Mining Understanding Data Visualisation
- Data Manipulation
- Dealing with Significant Amounts of Data
Who really ought to sign up for this course in Data Analysis?
Anyone who is interested in analyzing data and finding any improvements or problems can earn a certification in data science analytics, which has been developed specifically for them.
The Data Science Analytics class does not require any prior knowledge or experience to enroll.
Overview of the Data Science and Analytics Course
The multifaceted field of data science is characterized by the integration of multiple scientific methods, systems, and processes in order to derive knowledge from different kinds of data. A data scientist takes the information that has been gathered and uses it to uncover new data courses, such as revenue, testimonials, and product information.
The importance of data analytics can be attributed to the fact that it assists firms in improving their performance. If it is integrated into the business model, then organizations will be able to assist in the reduction of expenses by determining ways in which they may do business in a more effective manner and by storing enormous amounts of data. Data analytics allows a firm to not only make better business decisions but also to help assess customer trends and satisfaction, which can lead to the development of new products and services that are both new and improved.
Data Analysis Steps
The process of analyzing data is comprised of a number of distinct processes, including the following:
- The first thing that has to be done is to figure out the requirements for the data or how the data should be categorized. The data can be broken down into categories such as age, demographics, income, or gender. The values of the data might be represented numerically or broken down into categories.
- The process of gathering the data is the second phase in the analytics of the data. This is something that may be accomplished through the use of a wide variety of resources, including computers, online sources, cameras, environmental resources, and individuals.
- After the data have been gathered, they need to be arranged before they can be examined. This might take place on a spreadsheet or some other kind of computer program that is able to process statistical data.
- After that, the data are made more presentable before being analyzed. This implies that it gets cleaned up and verified to verify that it does not contain any errors or duplicates and that it is not missing any necessary information. Before sending the information to a data analyst for analysis, this process helps fix any errors that may have been made.