Data Science Course

While a good academic background provides an advantage to those interested in a data science profession, it is not the only criterion needed to be successful. Anyone with a basic education background and an intellectual curiosity about the subject matter can start a career on this path.

We have a specially designed IT basics training program for beginners to complete before the main program begins. In terms of IT training for newcomers, what makes us unique is that applicants do not have to go through a technical elimination process before starting our programs. We’ll simply start with a communication skills assessment to get to know our students better- ALL skill levels and backgrounds are welcome!

What we want from our participants is motivation, commitment, discipline and hard work to enable them to distinguish themselves as professionals in the IT market.

With this program, you will acquire skills in Data Science topics such as machine learning, statistical analysis, and data analytics. You will also gain experience with relevant industry tools and technologies such as SQL, Tableau and Python.

We offer several payment options to make the program work for you:

• Full/advance discount
• Installment payment option (various term options)
• Other payment options

This program prepares you for exciting IT roles such as Data Engineer, Business Analyst, Data Analyst, Data Scientist and more…

The data science course prepares you to work as a Data Scientist, extracting knowledge and insights from various data formats, building composite statistical algorithms and synthesizing massive data.

These Data Science jobs allow you to work in a variety of areas including e-commerce, gaming, healthcare, manufacturing, transportation, banking, finance, etc.

There are no prerequisites for Data Science with IT Fundamentals (IT Fundamentals + Module 1 (Data Analytics) + Module 2 (Machine Learning & Deep Learning & NLP)) program.
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In the United States, the average salary for a data analyst intern is $73,675.

About 3 thousand billion bytes of data are created every day and this rate is only increasing. However, much of those billion bytes of data lie dormant, waiting to be used. That’s why data science jobs are among the technology industry’s fastest growing and most in-demand industries.

Data Science is the field of acquiring, processing and making useful this enormous amount of data. In other words, it is a discipline that uses computer science and statistical methodology to produce meaningful predictions and gain insights into various industries.

In this Data Science Bootcamp you will learn how to extract knowledge and insights from different types of data, create complex quantitative algorithms, and synthesize vast amounts of information. You will also develop the leadership and communication skills required in this cross-disciplinary sector to build on the core competencies of a Data Scientist. At the end of the training you will know how to:

• Recognize critical questions in your field
• Collect relevant data from different sources using the mastered tools
• Store and manage data
• Comprehend valuable data
• Converting results into business solutions
• Show the findings that will benefit the company

You can become a Data Science professional through various training methods and collegiate programs such as traditional bachelor’s/master’s degrees, certificate programs (IT Bootcamps), and online education platforms.

Our Clarusway Data Science Course provides expert training with an instructor for a very specific curriculum over a short period of time. It is a fast track to a successful IT career for those who need to save their budget and time. This course is a part-time/full-time program that requires daily study through pre-class work, in-class instruction, and post-class activities. We also offer behind-the-scenes lab work and mentorship sessions. Our LMS (Learning Management System) linked to a C

MS (Career Management System) provides the path for a successful launch into a new IT career – or an upskilling opportunity for professionals with some IT experience.

You can learn data science by accessing educational websites or YouTube videos. However, without the help of a professional team, mentoring, planning lessons, it is difficult to maintain the discipline needed to start a career. Without hands-on projects and highly trained instructor guidance, most students will struggle alone.

Data science can be a stressful job due to its inherent problems. Stress depends on the circumstances, the workplace culture and the nature of the project. Those who are passionate about their work love it, while others may find it stressful. We notice that IT professionals who have been thoroughly trained take confidence into a new career. When an IT professional thrives, job satisfaction can be found through successful project completion, positive management feedback, and promotions in both pay and position. Stress levels are lower when subject mastery is achieved! A Data Scientist is uniquely positioned to influence corporate decision making for business growth. Stress is a highly subjective feeling – we guide individuals to be successful in launching their new careers.

The average salary of a data analyst is $123,233 per year in the United States.

Data Science presses are paid well because companies have a wealth of data to derive value from. In addition, the digital world requires the ability to derive insight from enormous amounts of data for various applications. This ensures that the value of Data Science press increases day by day. It is predicted to be a growing field in the coming years.

Data analytics is mainly concerned with contextualizing historical data, while data science is more concerned with machine learning and predictive modeling. Data science is a multidisciplinary field that includes algorithm development, data inference, and predictive modeling to address challenging business problems. On the other hand, data analytics encompasses a number of different subfields within the broader field of statistics and analytics.

In other words, data analysis is a more focused and precise discipline than data science.

Data analysis involves answering questions asked to assist in decision making. It uses existing data to uncover useful facts. Data analysis is a discipline that focuses on specific regions with specific objectives.

On the other hand, data science is concerned with identifying new problems that you may not have known needed to be addressed to drive innovation. Unlike data analysis, which focuses on testing a hypothesis, data science focuses on making connections and molding questions to provide future answers.

To put it in an analogy, data science is a factory made up of the methods and tools; data analysis is a specific production line. Focusing on data science without learning data analytics is like trying to produce by bypassing the factory production line.

While this varies based on the organization and scale of the project, data scientists often earn more because they are more skilled and experienced.

It’s up to your wishes, goals and skills. Know your differences. Data analytics mainly focuses on contextualizing historical data, while data science focuses on machine learning and predictive modeling. You can take your career beyond data analysis by learning new data skills and becoming a Data Science professional.

Data Scientists are the people who do data science. In other words, Data Scientists explore data and strive to innovate based on analyzing how things have happened historically (or finding a fresh new concept to drive innovation forward!).