Data Science Tutorials

Data Science Tutorials For Beginners and Professionals

In this Data Science Tutorials Course For Beginners and Professionals article series, we discussed all the basic, intermediate, and advanced concepts of Data Science with simple as well as real-time examples. Each and every concept will explain with simple as well as real-time examples. 

Overview of this Data Science course

Data science has the highest demand across all industries, and the need for professionals and practitioners is also booming. If you have a keen understanding of analytical skills, chances are great to become a data scientist or data engineer. This professional course will guide you through the basics and jump-start your career in data science. This course covers basic concepts used in Data science like Big data, R programming, HADOOP, Apache Spark, machine learning, Python, etc. This course will introduce you to the concepts of data science and what data scientists actually do. 

At the end of the course, we assign you the project work which will test your understanding of the course. These hands-on assignments will help you build a portfolio using real-world problems, use cases, and data science tools. 

Throughout this course, we will be using the R and Python programming environment. You will learn Python, R, statistical concepts, and data analysis techniques simultaneously. 

The objective of this Data Science course

Following are the objectives of the data science training course:

Learn tools and techniques for Transformation of Data

As a data scientist, it is important to know about the transformation of data. Transformation is the process of changing the format, structure, or values of the data. It’s similar to the cooking process. Let’s consider raw rice as source data in a format, where we transform raw rice to cooked rice i.e source data in another format to make it compatible to digest i.e. destination. This course will introduce you to tools and techniques that make the transformation process easy.

Data analysis

Data analysis is the key skill that is required by a data scientist. Learning analytical skills is being very much simple with this course. You will be learning Big data technology like Hadoop.

Understand Data Mining

This process includes the extraction of information to identify patterns, trends, and useful data which will help organizations to make data-driven decisions from a huge set of data. That means you have to analyze lots of data. You will learn more about data mining in this course.

Understand insights about the Data scientist roles

To become a successful Data scientist, it is important that the person should have multi-tasking skills. Data scientists perform multiple roles like developer, analyst, a statistical expert. So, you should have held on to multiple skills to perform this role. Different functions will be taught in this professional course which will help you to perform multiple tasks at a time.

Understand Machine Learning Algorithms

If you are a developer, you might understand the importance of algorithms in software. If you are not a developer, no problem you will get to know in this course. Machine Learning is a trending technology in the industry. It is very much important for Data scientists to understand algorithms. So, this is the place where you will learn and understand the algorithms. 

Eligibility of the course

1. Any fresher with Bachelor’s degree and with an interest in the data science field. 
2. Any IT experience professional who is seeking to get a job and has an interest in data.
3. Student from any stream (B.E./B.Tech/BSC/MCA//M.Sc computers/Bcom/BCA)

Prerequisites of the course

Before starting this course, a person should have the following non-technical prerequisites:

1. You should have the curiosity to learn data science, understand business problems
2. Communication skills are important in every field to communicate with the team. So, you should have good communication skills.

Following are the technical prerequisites:

1. Understanding of mathematical modeling to solve mathematical calculations.
2. Understanding of statistics like mean, median, or standard deviation. Statistical study is very much important in data science.
3. Basic programming knowledge like Python, R. 

Course Duration

This is a fast-paced course with 30 days of learning to understand the concepts of data science and make it capable of solving complex business problems. After completing this fast-paced course you will be assigned real-time project work which will help you understand and make you professional in this field.

What do we expect from you?

We will do our level best to cover all the concepts related to Data Science, but in the meantime, if you have any specific concept in your mind that you want us to cover, then please leave it as a comment on the comment box, and we will definitely discuss that concept(s) in this Data Science Tutorials course.

Finally, your valuable feedback is very important and means a lot to us. So, if you have a few minutes, then please let us know your thoughts and feedback on this Data Science Tutorials course.

Course Information

Course Instructor

Dot Net Tutorials Author

Author: Pranaya Rout Pranaya Rout is a Senior Technical Architect with more than 11 Years of Experience, Microsoft MVP, Author, YouTuber, and Blogger eager to learn new technologies. Pranaya Rout has published more than 3,000 articles in his 11-year career. Pranaya Rout has very good experience with Microsoft Technologies, Including C#, VB, ASP.NET MVC, ASP.NET Web API, EF, EF Core, ADO.NET, LINQ, SQL Server, MYSQL, Oracle, ASP.NET Core, Cloud Computing, Microservices, Design Patterns and still learning new technologies.