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"AI to contribute $16.1 trillion to the global economy by 2030. With 133 million more engaging, less repetitive jobs AI to change the workforce." - (Source). Data Science with Artificial Intelligence (AI) is a revolution in the business industry.. AI is potentially being adopted in automating many jobs leading to higher productivity, less cost, and extensible solutions. It is reported by PWC in a publication that about 50% of human jobs will be taken away by the AI in the next 5 years.
There is already a huge demand for AI specialists and this demand will be exponentially growing in the future. In the past few years, careers in AI have boosted concerning the demands of industries that are digitally transformed. The report of 2018 states that the requirements for AI skills have drastically doubled in the last three years, with job openings in the domain up to 119%.
The period of our Data Analytics course in Noida is different from institute to institute, as it starts from 3 months to 6 months. The course includes theoretical knowledge as well as practical training, so a student would gain the right skills.
Anyone with an even remote idea about math and statistics can join it. Our course is ideal for freshers or those in mid-career interested in data-driven decision-making. No previous experience is required to enroll.
Yes, We do provide online classes. This flexibility allows students to learn at their own pace and gain access to course materials at any time, anywhere and even helps the working professionals.
On average, the class size is between 15 and 30 students, providing sufficient interaction and personalized attention from instructors, which has an excellent overall impact on learning and indicates an interactive session.
Now, after completing our course, there are various types of career opportunities that can be pursued. Graduates can perform a role such as data analyst or business intelligence analyst and even data scientist.
A fresh graduate will greatly benefit from the internship opportunity with AiSPRY that our institute offers. He will work on a live project and get hands-on experience of implementing a data analytics solution. This will improve his employability immensely. Most employers value live project experience only.
Statistics background is useful as in basic programming languages such as Python or R. However, most courses offer introductory sessions for people with a minimal background.
Multiple quizzes, projects, and practical assignments are also used to evaluate the students. These assessments are done to allow the students to understand both theoretical concepts and applications practically.
Yes, many programs offer guest lectures and workshops conducted by industry experts for students to get insight into trends, as well as provide networking opportunities within the field.
Support is also given to problem students through institutional support. We do help the students through providing them with mentors or support teachers. They ensure each student passes and helps those underperforming by giving them extra tutoring sessions and other supplementary resources.
Topics covered in the curriculum are visualization, statistical analysis, machine learning, data cleaning, programming languages, etc. That would ensure full coverage of all domains of data analytics.
Yes, Curriculum would place great emphasis on popular software tools in practice: Tableau, Excel, Python, etc. and hands-on experience there is no other alternative but their use in practice.
Many of our courses include real-world projects as capstone projects or real-world datasets that apply knowledge learned by a student to real work experience that can be applied in a way relevant to future employers.
Our institution will issue a certificate at the end of our course, indicating that students have acquired the skills and training and enhancing employability when they seek to enter the data analytics job market.
Indeed, there are courses that often form modules on communication, teamwork, and problem-solving skills-necessary skills for information presentation in a professional context.
The key objectives of this course are:
We do provide placement assistance, which may include resume workshops, interview preparation, and networking events in a bid to help connect students with possible employers in the data analytics sphere.
Yes, we do provide internships , most institutions can connect students to several opportunities developed through partnerships with companies with an aim of improving the practical experience, hence the employability of student.
Major campus recruitment happens across industries, and companies like TCS, Wipro, start-ups, which are actively hiring data analysts to drive their data driven initiatives.
The average salary for entry-level data analysts in Noida would be from INR 3 to 6 lakhs per annum, and one can expect it to grow as more experience is gained in the industry.
The field of data analyst jobs in Noida is rapidly expanding, offering opportunities across various industries like finance, healthcare, and e-commerce. Skilled analysts are in high demand for data-driven decision-making.
Salaries for data analysts in Noida typically range from INR 3 to 6 lakhs per annum for entry-level positions, with experienced professionals earning significantly higher based on skills and expertise.
Data analytics projects in Noida often involve real-world datasets, focusing on market trends, customer behavior, and operational efficiency. These projects help students and professionals apply analytical skills in practical scenarios.
Open-source tools in analytics play a crucial role by providing accessible, customizable solutions for data processing, visualization, and machine learning. They empower users to innovate without high software costs, enhancing collaboration.
Modes of training in data analytics include in-person classes, online courses, and hybrid formats. Each approach offers flexibility, catering to different learning preferences while providing essential skills through hands-on projects and lectures.
Data analytics is widely applied across industries such as finance, healthcare, retail, and manufacturing. It enhances decision-making, optimizes operations, improves customer experiences, and drives innovation through actionable insights derived from data.
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