Data Science

Data Science is an innovative field that involves the extraction of valuable insights and information from complex data sets. It ... Show more
40 Students enrolled
0 reviews
  • Description
  • Curriculum
  • FAQ
Datascience with ML.png

The course covers various topics such as data cleaning, data visualization, machine learning, and statistical analysis. With the help of these skills, students can analyze and interpret data to make informed decisions and predictions. Data Science is highly useful in today’s digital age as organizations are generating enormous amounts of data that need to be analyzed to gain a competitive advantage.


Data Science is an innovative field that involves the extraction of valuable insights and information from complex data sets. It is a multidisciplinary field that combines statistics, computer science, and business knowledge to help organizations make data-driven decisions. The course on Data Science with machine learning is designed to provide students with a comprehensive understanding of the tools and techniques used in this field.


Data Science is also in high demand, and the prospects for future employment are excellent. The field is expected to grow rapidly in the coming years, and there is a huge demand for skilled professionals who can work with data. Many organizations are investing heavily in data science, and there is a need for professionals who can work with big data, machine learning, and artificial intelligence.


In conclusion, the course on Data Science is an excellent investment for anyone who is interested in working with data. It provides students with the necessary skills and knowledge to analyze and interpret data, which is highly valuable to organizations.

Introduction to Data Science
Python Programming
Object Oriented Programming
SQL & Advanced SQL
Machine Learning - Part 1
Machine Learning - Part 2
Data Visualization
1. What is the difference between Data Science and Computer Science?
Data Science involves the analysis of large datasets using coding and statistics to find patterns in this data. Computer Science, on the other hand, involves using logic to write codes that will help complete tasks of varying levels of complexity.
2. Can I pursue a Data Science degree without Maths or Computer Science in my undergrad?
Even if you think you have previously struggled with mathematics, you can still master the data science math abilities. No doubt , Data Science requires an understanding of math, but the necessary Data Science math skills can be learned.
3. What do Data Scientists do?
The main job of Data Scientists is to analyze large amounts of data using artificial intelligence and statistics to make sense of it and to find patterns in this data, to be able to apply the derived knowledge in solving real-world problems.
4. Why is Data Science trending?
In this modern world, huge amounts of data is being produced every second. Data Science helps make sense of this data and is a professional career.
5. Can I go for a Data Science degree if my maths is not good?
Yes, you can! Majority of the people working in Data Science has similar level of math literacy, since it is handled by software and therefore does not require a high level of mathematical or statistical skill.
6. What are the main components of Data Science?
The main components of Data Science are data collection , data preprocessing ,data analysis and data visualization
7. What are the programming languages used in Data Science?
Some of the most popular languages used in Data Science are python , R , SQL .
8. How much machine learning is required for Data Science?
The quality of machine learning depends on the data provided and the algorithms' ability to analyze it. In the future, Data Scientists will be expected to have a basic understanding of machine learning. As a result, the capacity to examine machine learning is one of the most essential Data Science skills.
Course details
Duration 126 hours
Level Beginner

Working hours

Monday 9:30 am - 7.30 pm
Tuesday 9:30 am - 7.30 pm
Wednesday 9:30 am - 7.30 pm
Thursday 9:30 am - 7.30 pm
Friday 9:30 am - 7.30 pm
Saturday 10:00 am - 7.00 pm
Sunday 10:00 am - 7.00 pm