Data science course fees and duration at Web D School

Data science course fees and duration at Web D School

The interdisciplinary field of data science blends machine learning, artificial intelligence, and business analytics with programming, statistics, and business intelligence in order to extract meaningful information from vast amounts of data.

Data science is a new, expanding field with numerous possibilities.

Data scientists are in high demand since they have a wide range of skills that could be useful in a variety of fields, including healthcare, finance, retail, education, and many more. Since 2012, the need for data scientists has grown annually by 31%. Depending on the area and size of the firm, their annual average compensation in India ranges from 6 to 10 lacs.

Apply for jobs as a data analyst, business intelligence analyst, data visualizer, etc. if you have experience in data science.

Data science is among the top five professions that young people worldwide want to pursue, and this tendency will persist over time.

Web D School is Chennai's best training ground for data science courses, but why is that?

1. Industry-specific instructors

All of our professors have extensive backgrounds in data science and have worked in recognized companies in the real world.

2. Small batch size

We only take six pupils in a batch so that we can give each one more individualized care.

3. An easy resume

We exclusively cover the material that a student needs to know in order to work in the field of data science, as opposed to other institutions that try to entice students with glitzy terminology and irrelevant topics.

4. Project-based instruction (SOAP)

We give our students a lot of activities and tasks as well as helpful comments using a process we call SOAP (Student Output Assessment Plan).

5. Live Interactive sessions

Because our batch sizes are small and the learning environment is truly participatory, we encourage our students to ask as many questions as they have during class.

6. Recorded discussions

Each lesson would be recorded on video and given to the students so they could watch and take notes later.

7. Placement support

From writing their resumes to finding fantastic jobs, our dedicated placement department supports all of our students.

Before enrolling in our data science training program in Chennai, there are a few things you should know.

DATA SCIENCE
The term "data science" broadly refers to data analytics, data mining, and machine learning. A data scientist is a specialist responsible for gathering, analyzing, and interpreting vast amounts of data. Data scientists frequently employ increasingly sophisticated data methods to forecast the future while coping with uncertainty.

a data analyst

Data analytics is a discipline within data science. A data analyst looks at data to find important details about a company's customers and solutions to issues. Using tools like SQL, R, or Python programming languages, data visualization software, and statistical analysis, data analysts commonly use structured data to address real-world business concerns.

the display of data

Visualizing data is a component of data science. Data visualization is the visual representation of information and data. Data visualization tools let users easily spot and understand trends, anomalies, and patterns in data by using visual elements like charts, graphs, and maps. Some of the most popular tools for data visualization are Tableau, Power BI, and Excel.

PYTHON

Python is a vital part of the toolkit for a data analyst since it is excellent at performing repetitive processes and manipulating data, and anyone who has worked with large volumes of data is aware of how frequently repetition occurs. You should research libraries like NumPy, Pandas, and Matplotlib that assist data analysts in doing their jobs once you have a good grasp of the fundamentals of Python. Tensorflow, Keras, and Theano are just a few of the many Python tools available to help data scientists build deep learning algorithms.

Calculus and Statistics

Math and statistics are essential to data science since they serve as the basis for all machine learning algorithms. Data scientists use statistics for data collection, evaluation, analysis, and conclusion-making. Additionally, they employ the appropriate numerical mathematical models and variables. Linear algebra can be effectively used to carry out a number of critical tasks.

USE OF COMPUTERS

Machine learning automatically evaluates and analyzes large amounts of data. It automates data processing and generates present-day forecasts without the need for human input. Real-time prediction training is done after an automated process of building data models.

SQL

SQL is a programming language used for managing and searching relational databases (Structured Query Language). When working with data that is kept in a database, SQL can, among other things, update and remove entries, as well as build and change tables and views.

EXACT LEARNING

Deep learning is a key component of data science, which also covers statistics and forecasting. Deep learning, a kind of machine learning, enables computers to carry out activities that people typically carry out, like speech recognition, image recognition, and prediction making. The ability to categorize, identify, locate, and describe data-based items is enhanced.

GENUINE INTELLIGENCE

In order for machines to be capable of making wise decisions in difficult circumstances, artificial intelligence's main objective is to simulate human intelligence via computers. Data science and artificial intelligence are combined in machine learning, where artificial intelligence is a tool for data science.