Hello there,

Here is the information regarding your question:

1. KIIT M.Tech CSE in Data Analytics Review

• Strengths : KIIT offers a well-structured program with a strong focus on practical applications, collaborations with industries, and good placement records. Companies like TCS, Cognizant, and Infosys recruit from KIIT.
  
  
• Weaknesses : Limited exposure to niche analytics tools compared to top-tier institutions.
  
  
• Overall Verdict : A good option if you’re looking for a balance of quality education and decent placements without GATE.
  
  2. Top M.Tech Data Analytics Colleges Without GATE
  
  
• BITS Pilani (Work Integrated Learning Programs) : Renowned for its flexible, industry-oriented programs.
  
  
• VIT Vellore : Offers M.Tech programs with specializations in Big Data Analytics. Admission is based on its own test (VITMEE).
  
  
• SRM University : Offers programs in Data Analytics with industry tie-ups.
  
  
• Manipal Academy of Higher Education : Focuses on practical learning and internships.
  
  3. Best Private M.Tech Data Analytics Colleges
  
  
• BITS Pilani
• VIT Vellore
• Amity University
• UPES Dehradun
  
  4. VIT vs. KIIT vs. SRM vs. Manipal vs. BITS Hyderabad
  
  
• Academics : BITS > VIT > Manipal > SRM > KIIT
• Placements : BITS > VIT > Manipal > SRM > KIIT
• Industry Exposure : BITS > VIT > Manipal > SRM > KIIT
• Verdict : If feasible, choose BITS Hyderabad or VIT.
  
  5. VIT M.Tech Big Data Analytics vs. AIML
  
  
• Big Data Analytics : Best for those interested in data engineering, data visualization, and business analytics roles.
  
  
• AIML : Ideal for students targeting AI/ML engineering, research roles, or AI startups.
  
  
• Recommendation : Choose based on your career goals. AIML has a slightly higher demand in tech industries.
  
  6. Best Online Options for M.Tech in Data Analytics
  
  
• BITS Pilani WILP : M.Tech in Data Science & Engineering.
• IIT Madras (Online Degree) : BS in Data Science, upgradeable to M.Tech.
• Great Lakes Institute : PG Programs in Data Analytics & AIML.
• Simplilearn & Coursera : Partnered with top universities for certifications.

For detailed reviews, visit the respective college websites or forums.

I hope this answer helps you. If you have more queries then feel free to share your questions with us we will be happy to assist you.

Thank you and wishing you all the best for your bright future.

1. Best GATE-free M.Tech college for data science with the best placement?

Here are a few of the top M.Tech colleges for data science which have good placements, and are also GATE free:

Indian Institutes of Technology: A number of IITs offer M.Tech data science or related fields in their colleges. The admission process is based on the entrance exam. For example: IIT Delhi - M.Tech/MS in MINDS, IIT Bombay - M.Tech in CSE (Data Science Specialization)

National Institutes of Technology (NITs): Some NITs provide M.Tech degree in the field of data science or related disciplines through separate entry tests. Example: NIT Trichy - M.Tech in Data Science Birla Institute of Technology and Science (BITS Pilani): Provides M.Tech degree in the field of data science through BITSAT - BITSAT Entry Test.

International Institute of Information Technology (IIITs): Some IIITs provide M.Tech programs in data science.  Some of them conduct their entrance exams. For instance, IIIT Hyderabad offers M.Tech in Data Science.    Private Universities: Many other well-known private universities are offering M.Tech programs in Data Science through their entrance exams. For example, Vellore Institute of Technology (VIT), Manipal Academy of Higher Education (MAHE)

Research should be done on each program regarding the curriculum offered, the faculty expertise, and the placement record before applying. You can find all information on their official website.

2. Best M.Tech college without GATE with the best placement for a data analyst?

Data Science courses usually cover concepts and skills involved in data analysis. Still, some colleges may have more specialized M.Tech programs in Data Analytics.

Use the list in question 1 as a reference. Many colleges which offer M.Tech Data Science also serve aspiring Data Analysts.

3. Is Big data analyst and data analyst course are different?

Yes, There are some key differences between Data Analyst and Big Data Analyst roles:

Data Size: Data Analysts typically work with smaller datasets, while Big Data Analysts manage massive datasets requiring specialized tools and techniques.

Skills: The areas of data cleaning, analysis, visualization, and communication are the core focus areas for Data Analysts. Big Data Analysts will also need knowledge of Hadoop, Spark, and distributed processing frameworks.

Career Paths: Data Analysts may progress to Business Intelligence or Data Science roles. Big Data Analysts may specialize in areas like cloud computing or data engineering.

However, the line may blur in practice. Some M.Tech programs might offer a data science curriculum with modules focused on big data processing.

4. Review of KIIT CSE in Data Analyst and how is the placement?

KIIT CSE offers an M. Tech curriculum in Computer Science and Engineering (CSE) with specializations in Data Science. Though data analyst is not mentioned explicitly, you can expect data analysis skills to be a part of the curriculum.

You can research KIIT CSE for Data Analyst Placement as follows:

KIIT Website: Check the KIIT website for details regarding the Data Science specialization within their M.Tech program in CSE. Placement reports might be available.

Reviews and Forums: Search online for reviews and discussions from alumni or current students about KIIT CSE and data science placements.

Contact KIIT: Consider directly contacting the KIIT admissions office or department to inquire about the program's focus within data science and potential career paths for graduates.

5. VIT vs KIIT VS SRM

These three universities are quite famous for engineering and technology education. Let's just compare briefly to help decide:

Criterion    VIT     KIIT     SRM

Reputation    National & International Recognition    Strong Reputation in India    Improving Reputation

Programs Offered    M.Tech in Data Science (through VITMEE)     M.Tech in CSE (Data Science Specialization)     M.Tech in Data Science

Placements    Historically Strong Placements    Good Placements    Improving Placements

Fees    High Fee Structure     Moderate Fee Structure     Moderate Fee Structure

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Important Note: This is a general comparison. Specific program details, faculty expertise, infrastructure, and placement records may be significantly different within each university.

Do the following:

Visit the websites for each university: Look up the specific data science programs taught, curriculum details, faculty profiles, and any placement reports that are available.

Consider factors important to you: Consider fees, location, infrastructure, duration of the program, and specific topics in data science that may interest you.

Look for online reviews and resources:

you need to fill number of months for which you have work ex and may be domain of work ex as well in cat form.write the industry within which you are currently working or which is the closest option you have.basically Forensic science is a multidisciplinary field so you can add this also, you must have salary slip, joining letter,work experience letter if you are claiming it.

BEST OF LUCK!!!

Well I think you forgot to mention the important part. Which is whats the goal. Exposure is a wide Answer. All are professional qualifications which give you professional experience. And the same ICWAI that you pursued also gave you professional exposure. But if my guess is that you want to get exposure in the same field then the relevant qualification would be CIMA and learning skills like financial modeling. (https://mentormecareers.com/what-is-financial-modeling/)

Science Stream (PCM):

• Physics (P): Essential for computer engineering and data analysis.
• Chemistry (C): While not directly related to data analysis, it can develop strong analytical thinking skills.
• Mathematics (M): Crucial for computer engineering, data analysis, and the logical thinking required in business.

Commerce Stream (MEC):

• Mathematics (M): As mentioned above, important for various aspects of your goals.
• Economics (E): Provides a foundation for understanding business principles and markets.
• Computer Science (CS): Introduces you to programming and computational thinking, valuable for both computer engineering and data analysis.

Benefits of Each Stream:

• Science Stream (PCM): Provides a strong foundation in core sciences and mathematics, which is crucial for computer engineering and data analysis.
• Commerce Stream (MEC): Equips you with business knowledge and introduces computer science, potentially sparking further interest in these fields.

Additional Considerations:

• Creative Writing: While not a formal subject in Class 11 and 12, you can pursue creative writing independently through online courses, workshops, or personal projects.
• Psychology: Similar to creative writing, consider online resources or introductory psychology courses offered by some institutions to explore this field further.

Beyond Class 11 and 12:

• Bachelor's Degree: Choose a program that aligns with your dominant interests - computer engineering, business, data science, or a combination (e.g., B.Tech. in Computer Science and Business Analytics).
• Online Courses: Take advantage of online courses in creative writing, psychology, or other areas of interest to continue exploring them alongside your main field of study.
  
  I hope it helps!

Correct Answer: Both Assertion A and reason R are correct but the reason R is the correct explanation of Assertion A

Solution : Answer = Both Assertion A and reason R are correct but reason R is the correct explanation of Assertion A

Long-term and short-term solvency of an enterprise can be assessed on the basis of financial statement analysis. Such analysis is done by a securities analyst who is interested in cash-generating ability, dividend payout policy and the behaviour of share prices.
Hence, the correct option is 2.

Hello,

Yes! There is potential for it, but not much.

One should be aware that a financial analyst's job include doing financial analysis in a variety of financial fields, including mergers and acquisitions, financial reporting, financial modelling, credits, etc. Additionally, this calls for prior expertise in a variety of fields, including corporate finance, accounting, and Microsoft Excel (because Excel is used for the majority of financial research).

Therefore, if an engineering graduate (or any graduate, for that matter) is offered a position with a company in the finance department after graduation, he or she should first consider gaining some years of experience while also obtaining some certifications, and only then should they consider pursuing an MBA in finance (which may be an Executive MBA or full-time MBA) or CFA ( Chartered Financial Analyst).

Thank You

Hello,

Analysts in quality control check and evaluate the product's quality. The function of a quality control analyst is to enhance and evaluate product performance.

You'll normally start your job as a quality control analyst at the entry-level after earning a bachelor's degree in chemistry or a closely related discipline. In general, a four-year bachelor's degree in a relevant field is required to work as a quality control analyst.

So, You are eligible to take that course.

Thank You

hello, i am sorry to hear that you could not clear Government exams, but there is always hope as there are still many career options left for you to pursue. However, you must devise a career plan. You want to become a data science or analytics, these are two different things once you get into the details of it, Data analytics is more specific and concentrated than data science . Data analytics focuses more on viewing the historical data in context while data science focuses more on machine learning and predictive modeling.

To become succesful in either of these fields,  you must have some key skills in your arsenal ;

• Statistical analysis and computing.
• Machine Learning.
• Deep Learning.
• Processing large data sets.
• Data Visualization.
• Data Wrangling.
• Mathematics.
• Programming.

yes, the pay is good of a data scientist or an analyst but it is not easy to become one .So, if you are confident that you can learn all these and much more. Then you should go for it but since you said you hardly have any computer knowledge, it could be difficult for you. take you time and then come to a well thoughtand evaluated  decision.

Hi , you can check this link,

https://www.google.com/url?sa=t&source=web&rct=j&url=https://dqxeclau.top/courses/business-analytics-course&ved=2ahUKEwjE2tvY66z4AhULwzgGHahuClwQFnoECCcQAQ&usg=AOvVaw3_2LzuGcuWznLH8c3UiHQo

If you have any other queries, feel free to ask.