HRDF HRD Corp Claimable Data Science Training
100% HRDF / HRC Corp Claimable Data Science Training
15-17 July 2024 – 9am till 5pm
What is Data Science process?
What is a data science course? Data science is simply defined as an interdisciplinary field of research that uses scientific processes, methods, methods, systems, and algorithms to extract the necessary knowledge and information from structured and unstructured data. The data science course has three main parts: big data, machine learning, and data science modeling. The main topics of data science courses are statistics, coding, business intelligence, data structure, mathematics, machine learning, algorithms, etc. Read this blog to learn more about all of the Data Science Programs for Beginners, Course Topics, and the IIT Curriculum for HRDF Claimable Data Science Training Course.
Best HRDF HRD Corp Claimable Data Science Training Course in Malaysia
HRDF HRD Corp Fully Claimable HRDF HRD Corp Claimable Data Science Training Course is 100% Claimable for You
Why study data science?
With the amount of data being generated and the development of the field of analytics, data science has become a necessity for businesses. In order to take full advantage of data, companies from different fields, be it finance, marketing, retail, IT or banking. Everyone is looking for data scientists. This has created a great demand for data scientists around the world. With the salary the company has to provide, IBM has announced that it will be a hot job in the 21st century. For a lot of people, this is a lot of work. In this field, people from all walks of life can pursue a career as a data scientist.
Components of data science
Data science consists of three parts:
Machine Learning – Machine learning comprises mathematical models and algorithms and is mainly used for machine learning and to prepare for daily work. For example, time-series forecasting is widely used in business and financial systems today. This allows the machine to predict the results of the coming months or years based on historical data models. This is a machine learning application.
Big Data – People generate large amounts of data on a daily basis in the form of clicks, orders, videos, images, comments, articles, RSS feeds, etc. This data is generally unstructured and is often referred to as big data. Big data tools and technologies primarily help convert this unstructured data into a structured form. Suppose someone wants to keep track of the prices of various products on an ecommerce website. You can use the web API and RSS feeds to access the same product data from different websites. Then convert them to a structured form.
Business Intelligence – Every company has and generates too much data every day. This data is carefully analyzed and then presented in a visual report in graphical form so those good decisions can be made. After carefully examining the patterns and details contained in the report, this can help management make the best decisions.
Introduction to Data Science Training Course
- Math and statistics skills
- Machine learning
- Algorithms used in machine learning
- The statistical foundations of data science
- Data Structures and Algorithms
- Scientific Computing
- Optimization technology
- Data visualization
- Matrix calculation
- School model
- Experimentation, evaluation and project deployment tools
- Use clustering for predictive analysis and segmentation
- Applied Mathematics and Computer Science
- Exploratory data analysis
- Business acumen and artificial intelligence