Techno Study
Data Science Bootcamp
6-month-long intensive bootcamp
Why Become a Data Scientist?

If you're looking for an exciting career offering stability and generous compensation, look no further!

Prestige, Salary, and Career Potential

Today, data science and AI are essential parts of many industries. Over the past few years, the global focus has shifted more and more towards data, and the new-age tech fields like Artificial Intelligence and Data Science have seen significant growth.

"The sexiest job of the 21st century" by Harvard Business Review.

The accelerating volume of data sources, and subsequently data, has made data science one of the fastest-growing fields across every industry. As a result, it is no surprise that the role of the data scientist was dubbed "the sexiest job of the 21st century" by Harvard Business Review.

The demand and salary of data scientists are growing remarkably.

According to Glassdoor and Forbes, demand for data scientists will increase by 28 percent by 2026, which speaks of the profession's durability and longevity, so if you want a secure career, data science offers you that chance.

Glassdoor placed it #1 on the 25 Best Jobs in America list.
How to Become a Data Scientist?
As mentioned, there is a great demand for professionals who can turn data analysis into a competitive advantage for their organizations. You create data-driven business solutions and analytics in a career as a data scientist.

To become a data scientist, you'll need to master skills in the following areas:
Learn statistics.
Statistics is the science concerned with developing and studying methods for collecting, analyzing, interpreting, and presenting empirical data.
Data visualization integrating different data sets and creating a visual display of the results using diagrams, charts, and graphs using BI tools such as Tableau and Power BI.
such as Apache Spark, and Hadoop, which are used to deal with large and complex data which can't be dealt with using traditional data processing software.
Providing systems with the ability to automatically learn and improve from experience without being explicitly programmed to. Machine Learning can be achieved through various algorithms such as Regressions, Naive Bayes, SVM, K Means Clustering, KNN, and Decision Tree algorithms, to name a few.
which involves cleaning, manipulating, and organizing data. Popular tools for data wrangling include R and Python.
Python is an open-source general-purpose programming language. Python libraries like NumPy and SciPy are used in Data Science and AI.
Master at least one programming language. 
which is required to store and analyze data using tools
Gain database knowledge
The field of data science is constantly evolving, so data scientists must be willing to learn new methods and techniques continuously. Therefore, a willingness to learn is essential for anyone interested in becoming a data scientist.
A willingness to learn:
Develop the ability to visualize results.
Having a working knowledge of Big Data tools
Master the concepts of Machine Learning.
Learn Data Wrangling
Where Do You Fit in Data Science?
Data science allows you to focus on and specialize in one aspect of the field. Here's a sample of different ways to fit into this exciting, fast-growing field.
Data Scientist
  • Job role: Determine what the problem is, what questions need answers, and where to find the data. Also, they mine, clean, and present the relevant data.
  • Skills needed: Programming skills (Python, R), storytelling and data visualization, statistical skills, knowledge of Hadoop, SQL, and Machine Learning.
Data Analyst / Business Intelligence Analyst
  • Job role: Analysts bridge the gap between the data scientists and the business analysts, organizing and analyzing data to answer the questions the organization poses. They take the technical analyses and turn them into qualitative action items.
  • Skills needed: Statistical skills, programming skills (Python, R), plus experience in data wrangling and data visualization.
Data Engineer
  • Job role: Data engineers focus on developing, deploying, managing, and optimizing the organization's data infrastructure and data pipelines. Engineers support data scientists by helping to transfer and transform data for queries.
  • Skills needed: SQL and NoSQL databases (MySQL, MongoDB), programming languages such as Python, Java, and Scala, and frameworks (Apache Spark, Hadoop).

Who can join the course?
We welcome everyone willing to learn software testing, especially graduates and residents who recently moved to the US and want to launch an IT job.
Why study this program?
Learn Python, Machine Learning, Big Data and soft skills only in 6 months, and with our career support, acquire a new profession.
What awaits graduates?
In-demand,high-paying remote jobs with a salary of more than $100,000 a year.

Our alumni work at

Tuition fee
Pay in 6-month-installments during the course and the rest after starting a job.
Save money for paying upfront.
Pay half of the tuition during the course and the rest after landing a job.
One-time payment
Join a 6-month bootcamp. Learn online with a flexible
schedule and convenient payment options.
We offer the best deal:
Program Structure
Data Visualization and Business Intelligence
Machine Learning
Python for Data Science
Python Fundamental
Web Scraping
Supervised and Unsupervised Learning
Classification Algorithms
Clustering Methods
Regression Models
Dimension Reduction
Model Selections
We are here for you!