Enrolling in a data science online training course from a prestigious institution such as the Indian Institute of Technology (IIT) guarantees that we will be learning from experts in the field. IIT Roorkee’s Data Science and Machine Learning Course is one of the best data science online courses available. The course covers the essential concepts that are essential to any data science online training, such as machine learning algorithms, linear regression, data visualisation, and communication. Completing the course can open up the doors to a prosperous and fulfilling **data scientist career**.

However, before we begin our journey with The **IIT Roorkee Data Science Online Course**, we need to be familiar with foundational concepts of data science that can make our learning journey smoother. Mastering these concepts beforehand will also enable us to understand the IIT Roorkee Data Science Online Course better and help us make the most of it.

Table of Contents

- 1 Here's a list of 10 must-know concepts for our data science online training:
- 1.1 1. Datasets
- 1.2 2. Data Cleaning & Pre-Processing
- 1.3 3. Data Science Tools & Technology
- 1.4 4. Machine Learning
- 1.5 5. Regression & Classification
- 1.6 6. Data Visualisation
- 1.7 7. Natural Language Processing
- 1.8 8. Big Data
- 1.9 9. Mathematical & Statistical Concepts
- 1.10 10. Data Science Real-World Applications

## Here's a list of 10 must-know concepts for our data science online training:

### 1. Datasets

The most basic yet most important concept we must know is the dataset. A dataset is a collection of data points, usually consisting of different variables such as numerical values and textual information. Datasets are an essential part of data science and machine learning projects because they provide the information needed to train models. Understanding how to select, manipulate, and analyse datasets is crucial for data science online training.

### 2. Data Cleaning & Pre-Processing

Dirty and unstructured data can impede our data science projects. Data cleaning and pre-processing are the processes of making sure our datasets are in a usable state. It involves dealing with issues such as missing values, outliers, or incorrect data types.

### 3. Data Science Tools & Technology

Data science tools and technologies such as Python, R, SQL, Tableau, Hadoop, and Spark are used to manipulate data and create models. It is important to understand the purpose of each technology and its advantages and disadvantages so that we can choose the right tool for the job.

### 4. Machine Learning

Machine learning is a subfield of artificial intelligence that enables computers to learn from data and make decisions without explicit programming. Understanding the basics of machine learning algorithms is a key concept for data science online training and IIT Roorkee’s Data Science Online Course.

### 5. Regression & Classification

Regression and classification are two of the most popular machine-learning algorithms used in data science projects. Regression is used to predict the outcome of a continuous variable such as stock prices or house prices. In contrast, classification can be used to classify data into different categories, such as spam or not spam.

### 6. Data Visualisation

Data visualisation is the process of transforming raw data into visual representations, such as charts and graphs. It is used to make data easily accessible and understandable to humans. With IIT Roorkee’s Data Science and Machine Learning Course, we can learn the fundamentals of data visualisation and use tools such as Tableau and D3.js to create stunning visualisations.

### 7. Natural Language Processing

Natural language processing (NLP) is a subfield of artificial intelligence that deals with understanding and generating human language using computers. It is a rapidly advancing field in data science, and many modern applications use NLP, such as chatbots and text-based search engines.

### 8. Big Data

Big data refers to large, complex datasets that cannot be processed using traditional methods. IIT Roorkee’s Data Science and Machine Learning Course will teach us how to use big data tools such as Hadoop and Spark to process, analyse, and visualise big datasets. Thus, we need to familiarise ourselves with big data concepts and technologies.

### 9. Mathematical & Statistical Concepts

Mathematical and statistical concepts are foundational for data science. We need to be strong in topics such as linear algebra, calculus, and probability to understand the underlying mathematics behind many data science algorithms.

### 10. Data Science Real-World Applications

Finally, we need to understand the real-world applications of data science. We can use data science for a wide range of tasks, such as predicting customer churn, forecasting sales, or detecting fraud. Being cognizant of the potential of data science can help us with projects in the **IIT Roorkee Data Science Online Course**.

Data science is a rapidly evolving field. As per estimates, the number of data science jobs is expected to increase by 28% in the next five years. In India alone, there will be about eleven million job openings in the data science field. Moreover, there is a shortage of data scientists in the job market globally.

Thus, embarking on a data science journey with **IIT Roorkee’s Data Science and Machine Learning Course** is a great way to develop the skills needed to stay ahead of the competition. Following the 10 must-know concepts outlined above, we will be well on our way to becoming successful data scientists!