Machine Learning: Machine Learning involves algorithms and mathematical models, chiefly employed to make machines learn and prepare them to adapt to everyday advancements. For example, these days, time series forecasting is very much in use in trading and financial systems. In this, based on historical data patterns, the machine can predict the outcomes for the future months or years. This is an application of machine learning.
Big Data: Everyday, humans are producing so much of data in the form of clicks, orders, videos, images, comments, articles, RSS Feeds etc. These data are generally unstructured and is often called as Big Data. Big Data tools and techniques mainly help in converting this unstructured data into a structured form. For example, suppose someone wants to track the prices of different products on e-commerce sites. He/she can access the data of the same products from different websites using Web APIs and RSS Feeds. Then convert them into structured form.
Business Intelligence: Each business has and produces too much data every day. This data when analysed carefully and then presented in visual reports involving graphs, can bring good decision making to life. This can help the management in taking the best decision after carefully delving into patterns and details the reports bring to life.
What is Data Science?
Data Science is a field that uses scientific approach, methods, and processes, algorithms to extract knowledge from many structured and unstructured data. It is expected that around 6 million data scientists will be required by 2021. With years of experience in technical training, PIMS provides full-fledged bestdata science courses in Noida with live projects and case studies.
If you are confused in how to start a career in Data Science, our Data Science training in Noida will guide you to achieve a higher position as a data scientist. Data Science experts are essential in almost every field from government security to industry experts.
Introduction to Data Science Introduction to Python Data Analysis Pipeline What is Data Extraction? Types of Data Raw and Processed Data Data Wrangling Overview of the Analytics Techniques, Business Analytics, Business Intelligence Industry Examples
We Provide various live projects for practice to our students, in consultation with our various industry partners in Marketing, Finance, Medical and other domains.
Data Science Course Certification
Tools Used
R
Python
MS Excel
R is used for data analysis, as a programming language, as an environment for statistical analysis, data visualization
Python is majorly preferred to implement mathematical models and concepts because python has rich libraries/packages to build and deploy models.
Microsoft Excel is considered a basic requirement for all data entry jobs. It is of great use in data analysis, applying formulae, equations, diagrams out of a messy lot of data.
Hadoop
SQL database/coding
Technology:
It is an open source distributed processing framework. It is used for managing the processing and storage of big data applications.
It is mainly used for the preparation and extraction of datasets. It can also be used for problems like Graph and Network Analysis, Search behaviour, fraud detection etc.
Since there is so much unstructured data out there, one also should know how to access that data. This can be done in a variety of ways, via APIs, or via web servers.
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Professional Institute of Marketing & Strategy-Best Institute for Digital Marketing Course in Noida,delhi,NCR. PIMS(Professional Institute of Marketing & Strategy) is a great learning platform for students, entrepreneurs and based at Sector 16, Noida.
For the past several years, PIMS has defined its leadership position in the education industry and helped students in learn SEO, Google Ads, Facebook ads and around 32+ more modules of digital marketing.