"I learnt Excel and VBA from Learnitix and it helped me in securing my career in MIS. I got the job in Pacesetters as Data Analyst and Gupta sir helped me so much in my CV and creating a profile on Naukri.com with proper keywords because of that i started receiving interview calls and finally got the job ."
"Awesome Trainer with Mindblowing Programming Skills.Trainer is superb and working professional and shares his personal experiences and challenges that you may come across while working on the data."
"The trainer is very supportive and friendly,he shares his all personal experiences and makes the students industry ready.I got the job in SLCM as MIS executive even before completing the course.Learnitix is a best place to learn."
Whether you should start with data analytics or data science depends on your goals, background, and interests. Both fields are closely related, but they have distinct focuses and skill requirements. Here's some guidance to help you decide: Data Analytics: Data analytics typically involves analyzing existing data to extract valuable insights and inform business decisions. It is more focused on descriptive and diagnostic analysis, meaning you're primarily looking at historical data to understand what happened and why. Data analytics often uses tools like Excel, SQL, and data visualization tools (e.g., Tableau, Power BI). If you're new to the field of data, data analytics is a great starting point. It's often considered the foundational step before diving into data science. Data Science: Data science is a broader field that encompasses data analytics but also includes machine learning, predictive modeling, and building data-driven products. Data scientists use a variety of programming languages (e.g., Python, R), machine learning libraries, and big data tools. Data science involves more advanced statistical and machine learning techniques to create predictive models and algorithms. If you have a strong background in mathematics, programming, and are looking to build predictive models or work on more complex data problems, you might consider starting with data science. Here are some factors to consider when making your decision: Your Background: If you're new to the field and have limited technical experience, starting with data analytics is often recommended. It provides a solid foundation in data handling and analysis. Career Goals: Consider your long-term career goals. If you aspire to work on predictive modeling, machine learning, and artificial intelligence projects, starting with data science may be more appropriate. Interests: Your interests matter. If you're excited about delving into data, choose the path that aligns with what you're passionate about.
100%. we will work on your data analytics skills and we will help you in creating the a perfect resume showcasing your skills with right keywords and ultimately ranking you resume on job portals search engines. You will 100% receive the calls from recruiters and we make sure you crack one.
Definately, you can pay the fees on monthly basis.
There is no pre-requisites for the said course as we start from 0.
Sure, you will be welcome to request your refund within 14 days of Payment.
No worries, In case you miss few classes you will be provided the back up classes for the same.
4 Months
You can learn in classroom or Online. Its your choice.
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