Data Analytics

Absolutely! Students from commerce or humanities backgrounds can definitely learn data analytics and excel in the field. While a background in math, statistics, or computer Science can be advantageous, it is not a prerequisite for learning data analytics. Here's how students from commerce or humanities backgrounds can approach learning Data Analytics Course .1. Gain a Solid Foundation:-  Start by building a foundation in relevant areas such as statistics, mathematics, and programming. This can be done through online courses, tutorials, or textbooks specifically tailored for beginners. Understand key concepts like data types, variables, descriptive statistics, and basic probability.2. Learn Data Analysis Tools:-  Familiarize yourself with popular data analysis tools such as Excel, which is widely used in commerce-related fields. Excel offers features for data manipulation, formulas, and basic statistical functions. Additionally, learn to use tools like R or Python, which are powerful programming languages for Data Analysis Training .3. Focus on Analytical Skills:-  Develop analytical thinking and problem-solving skills. Data analysis requires critical thinking, the ability to ask the right questions, and interpret the results. Practice analyzing real-world data sets, identifying patterns, and drawing meaningful insights.4. Take Relevant Courses:-  Enroll in online or in-person courses focused on data analytics. Many platforms offer courses specifically designed for beginners without a technical background. These courses cover topics such as data manipulation, visualization, statistical analysis, and machine learning.5. Apply Data Analytics in Real-World Contexts:-  Undertake projects or internships that allow you to apply data analytics skills in practical scenarios. This hands-on experience will strengthen your understanding and showcase your capabilities to potential employers.6. Leverage Resources:-  Take advantage of online resources, such as tutorials, blogs, and forums, to expand your knowledge and learn from experienced professionals. Participate in online communities or join local meetups related to data analytics to network with like-minded individuals and gain insights from their experiences.7. Continuous Learning:-  Data analytics is a rapidly evolving field, so embrace a mindset of continuous learning. Stay updated with the latest trends, tools, and techniques by following industry blogs, attending webinars, or participating in online courses.Remember that a diverse background can bring unique perspectives to data analytics. Skills like problem-solving, critical thinking, and effective communication, which are often developed in commerce or humanities fields, are highly valuable in data analysis. Many organizations value a well-rounded skill set that combines domain knowledge with analytical expertise.While it may take some extra effort and dedication to bridge the gap in technical skills, it is certainly possible for students from commerce or humanities backgrounds to learn and succeed in data analytics. With the right mindset, learning resources, and practical application, you can build a solid foundation in data analytics and open up exciting career opportunities in the field.Structured Learning Assistance - SLA is known for its excellence in education sector who provides Data Analytics Course fortified with a well established infrastructure with advanced lab facility, senior industry expert and modern training system to enhance the knowledge of students. SLA is well known entity having Data Analytics Institute. It is built with all convenient facilities and positive study ambiance for the students. Fulfill the main task of placement, SLA aids in 100% Job Placement after completion of 70% course.

Absolutely! Students from commerce or humanities backgrounds can definitely learn data analytics and excel in the field. While a background in math, statistics, or computer Science can be advantageous, it is not a prerequisite for learning data analytics. Here's how students from commerce or humanities backgrounds can approach learning data analytics:1. Gain a Solid Foundation:-  Start by building a foundation in relevant areas such as statistics, mathematics, and programming. This can be done through online courses, tutorials, or textbooks specifically tailored for beginners. Understand key concepts like data types, variables, descriptive statistics, and basic probability.2. Learn Data Analysis Tools:-  Familiarize yourself with popular data analysis tools such as Excel, which is widely used in commerce-related fields. Excel offers features for data manipulation, formulas, and basic statistical functions. Additionally, learn to use tools like R or Python, which are powerful programming languages for data analysis.3. Focus on Analytical Skills:-  Develop analytical thinking and problem-solving skills. Data analysis requires critical thinking, the ability to ask the right questions, and interpret the results. Practice analyzing real-world data sets, identifying patterns, and drawing meaningful insights.4. Take Relevant Courses:-  Enroll in online or in-person courses focused on data analytics. Many platforms offer courses specifically designed for beginners without a technical background. These courses cover topics such as data manipulation, visualization, statistical analysis, and machine learning.5. Apply Data Analytics in Real-World Contexts:-  Undertake projects or internships that allow you to apply data analytics skills in practical scenarios. This hands-on experience will strengthen your understanding and showcase your capabilities to potential employers.6. Leverage Resources:-  Take advantage of online resources, such as tutorials, blogs, and forums, to expand your knowledge and learn from experienced professionals. Participate in online communities or join local meetups related to data analytics to network with like-minded individuals and gain insights from their experiences.7. Continuous Learning:-  Data analytics is a rapidly evolving field, so embrace a mindset of continuous learning. Stay updated with the latest trends, tools, and techniques by following industry blogs, attending webinars, or participating in online courses. Remember that a diverse background can bring unique perspectives to data analytics. Skills like problem-solving, critical thinking, and effective communication, which are often developed in commerce or humanities fields, are highly valuable in data analysis. Many organizations value a well-rounded skill set that combines domain knowledge with analytical expertise.While it may take some extra effort and dedication to bridge the gap in technical skills, it is certainly possible for students from commerce or humanities backgrounds to learn and succeed in data analytics. With the right mindset, learning resources, and practical application, you can build a solid foundation in data analytics and open up exciting career opportunities in the field.Structured Learning Assistance - SLA is known for its excellence in education sector who provides Data Analytics Course fortified with a well established infrastructure with advanced lab facility, senior industry expert and modern training system to enhance the knowledge of students. SLA is well known entity having Data Analytics Institute. It is built with all convenient facilities and positive study ambiance for the students. Fulfill the main task of placement, SLA aids in 100% Job Placement after completion of 70% course. 

Congratulations on learning Advanced Excel! The next step depends on your specific goals and interests. Both Power BI and SQL are valuable skills that can complement your proficiency in Excel.Here's a breakdown of each option to help you make an informed decision:Power BI:Power BI is a business intelligence tool developed by Microsoft. It enables users to transform raw data into interactive visualizations and reports, allowing for powerful data analysis and storytelling. Learning Power BI can enhance your ability to analyze and present data effectively, making it a valuable skill for data-driven decision-making. If you're interested in data visualization, creating interactive dashboards, and sharing insights with others, Power BI is an excellent choice.SQL (Structured Query Language):SQL is a programming language used for managing and manipulating relational databases. It allows you to query databases, retrieve and manipulate data, create and modify database structures, and perform data analysis tasks. Learning SQL can be beneficial if you work with large datasets, need to extract specific information from databases, or want to gain a deeper understanding of data management and database systems. SQL is widely used across industries and is considered a fundamental skill in data analysis and database management.Consider the following factors when deciding which path to pursue:1. Goals and Interests:-  Consider your career aspirations and the areas of data analysis that interest you the most. If you enjoy working with visualizations and presenting data in a user-friendly manner, Power BI might be a better fit. If you're more inclined towards data manipulation, querying databases, and working with large datasets, SQL could be the right choice.2. Job Market and Industry Trends:-  Research the job market and industry trends to determine which skill is more in demand in your target industry. Assess job descriptions and requirements to identify the skills that align with your career goals.3. Complementary Skills:-  Consider how Power BI or SQL can complement your existing skills, including Advanced Excel. Think about which skill will enhance your current skill set and make you more versatile in data analysis and reporting.4. Personal Preference:-  Consider your personal preference and which skill you find more interesting and enjoyable to learn. This will help maintain motivation and engagement throughout the learning process.Ultimately, both Power BI and SQL are valuable skills in the data analysis field. Assess your goals, interests, and the requirements of your target industry to make an informed decision. It's also worth noting that you can learn both skills over time if you find them both relevant to your career path.Structured Learning Assistance - SLA institutes are known for their best coursework, experienced faculty, and strong industry connections, making them some of the best options for pursuing a data analytics course in India. 

BPP University entry requirements to study the MSc Management with Data Analytics course are as follows:A minimum of 2:2 Honors degree in a related subject (Example: STEM) from the UK or recognised international university ORA minimum of 2:1 Honors degree in a non-related subject from the UK or recognised international universityAlso, students are required to meet the English language requirementsTestsScores IELTS6.5 overall, with a minimum of 6.0 in no more than two components  PTE Academic70 overall, with a minimum of 64 in no more than two components  TOEFL iBT79 – 93 overall with:Reading: 13 – 18Writing: 21 – 23Listening: 12 – 19Speaking: 18 – 19After the review of the applications, students may be required to attend a face-to-face interview or Skype interview or take part in the telephonic interview.

The reasons to study BPP University MSc Management with Data Analytics course are given below:Experience using numerous data tools, theories, and techniques to undertake practical data and analytical activities that add value to any businessFocuses on practical knowledge and skillsContinuation of learning as technology changes, thereby, helping students to challenge existing structures and processesVarious opportunities in the areas like Business Analyst, Management Consultancy, Data, Marketing and OperationsIn short, students are going to benefit from an integrated academic and professional education experience. Furthermore, practical learning shall allow students to critically analyze complex situations using various data analytics tools and data visualization techniques

Being an Alumnus of LPU, I would like to tell you that LPU offers numerous courses in Engineering disciplines.B.Tech. (Hons.) (Computer Science and Engg. - Data Science & Data Engineering) in tie up with Trans Org Analytics.This programme aims towards creating skillful graduates with specialisation in Data Science and Data Engineering domain which emphasizes comprehensive knowledge through courses like data engineering, data visualization, data modeling, big data analytics and predictive analytics. The programme encompasses Data Science as an interdisciplinary, problem-solving oriented domain.Salient features of the programme are as follow:1.Specialization and Industry Certificationsa).12 - 16 Specialization courses.b).Industry Certifications are integral part of curriculum. Indicative Certifications:·         IBM Data Science Professional Certificate·         Google Professional Data Engineer Certification2.Seed Moneya).Upto Rs. 20,000/- per student for Designing a Programme/ Software/ Mobile App.b).Rs. 2 Lacs to Rs. 5 Lacs per project for StartUp/ Entrepreneurial Venture.c).Upto Rs. 10000/- Seed Grant for Innovation/ Research activities.3.Courses by Industry Expertsa).Around 40% courses to be taught in online/ blended mode by Industry experts.b).12 - 16 courses by Industry experts3.Bootcamps/ Datathons:Well-structured and short term, intense training sessions designed to prepare students for the practical reality through bootcamps. Students will be required to participate in various national and international competitions like Datathons.The Eligibility of the programme is 60% aggregate marks in 10+2 (with Physics, Mathematics and English) or equivalent, subject to qualifying LPUNEST or CUET.Every year more than 500 companies visit to the campus for the student placement.The highest package offered to the student is Rs 62.72 LPA and the average package is Rs 1.6 LPA.These are the companies which visit to the university are CISCO, D.E Shaw India, Oracle, Cognizant, TCS, Tech Mahindra, Wipro, Amdocs, Capgemini, Verizon, Cmware, Virtusa, Accenture, SAP Labs, Acko Technology Services, Tivo Corporation, Informatica, Infineon, Goodera, Rentomojo, Qualcomm, Dell, Deloitte, Drishti Soft Solutions, Tek Systems, Interviewbit (Scaler), LG Soft India, PEGA, Tavisca Solution, Hitachi Consulting, Blujay, Tesssolve, Code Nation, ITC Infotech, MAQ Software and many more.

The Bapatla Engineering College cut off for 2023 will be based on the Andhra Pradesh Integrated Common Entrance Test (AP ICET). The exam will be conducted by Sri Venkateshwara University, Tirupati on May 25, 2023, and, May 26, 2023. For the B.Tech admission, the Andhra Pradesh Engineering Agriculture and Medical Common Entrance Test (AP-EAMCET) is also accepted. The exam for the engineering stream is expected to be held in July 2023. Based on the scores of this test, the college releases the cut off list. This is followed by the various counselling rounds conducted by the college. The Bapatla Engineering College cut off is determined by various factors. These include:*The total number of candidates appearing for the TS EAMCET exam*The total number of seats available for each course at the college*The difficulty level of the exam*Previous years’ cutoff trends 

The total fees for the M.Tech. programme in Computer Science and Data Analytics at NIT Tadepalligudem is INR 1.40 Lakh. This includes tuition fees, as well as other fees and charges applicable for the duration of the program.The M.Tech. programme in Computer Science and Data Analytics at NIT Tadepalligudem offers a comprehensive curriculum designed to equip students with the necessary knowledge and skills in the fields of computer Science and data analytics. The programme covers topics such as data analytics, machine learning, data mining, and statistical modeling.The total fees of INR 1.40 Lacs cover various aspects of the program, including faculty guidance, access to laboratory facilities, course materials, and other academic resources. Additionally, it may also cover certain administrative and miscellaneous charges.It's important for prospective students to note that the fees mentioned are subject to change and it's recommended to refer to the official NIT Tadepalligudem website or contact the institute directly for the most up-to-date and accurate information regarding the fees structure and payment schedule.NIT Tadepalligudem aims to provide quality education and a conducive learning environment for students pursuing the M.Tech. programme in Computer Science and Data Analytics, ensuring that they receive value for their investment in terms of knowledge, skills, and future career prospects.