Data science is the branch that uses several methods and algorithms to get a deeper insight into the collected data. The idea is to help make informed decisions for businesses so that performance can be improved and value can be created. Another purpose of data science is to find solutions to complex problems in different fields like e-commerce, education, finance and healthcare, to name a few.
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Data science uses a lot of techniques, such as time series forecasting. This process analyses historical data and presents pattern and trend-based forecasts. The idea is to get an insight into past behavior and upcoming potential in various departments like customer demand, sales volumes, weather conditions and stock prices. You can head to Bangalore if you want to learn and gain experience in the field of data science with time series forecasting. The city is the centre of major IT hubs, allowing you to choose from several tech companies for data science training. The good thing is that these institutes provide relevant courses.
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This article discusses data science training with time series forecasting from different angles. We will talk about the demand for this skill in Bangalore and the skills and tools you need to be proficient in data science.
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The demand and scope of data science in Bangalore
In India, Bangalore is on the list of the most reputable IT hubs, with several tech startups and companies requiring data scientists. The good news is that data science offers a vast scope in several fields, like education, finance, healthcare, and e-commerce. In addition, startups and companies use data science to provide better products and services for customer satisfaction. Analytics India Magazine released a report at the end of 2020. According to this report, Bangalore is on top of the list when it comes to job openings in the field of data science. The city has a share of 23% of jobs offered for data scientists across the country. Moreover, the report reveals that the data science institutes in the city offer the highest median salary for these professionals. The major players providing these jobs in Bangalore include Amazon, IBM, Acenture, Myntra and Flipkart, to name a few.
The required skills and tools
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If you have made up your mind to jump into data science in time series forecasting field, you have to have the required knowledge. For instance, you must have solid knowledge in several fields, like programming, statistics, and mathematics, to name a few. Apart from this, it would be best if you had a lot of experience using a set of skills and tools to collect, process, analyze, visualize and model data. Now, let’s talk about the skills and tools you need to get started in the world of data science with time series forecasting.
Python:
Python is a programming language used in the data science field. This coding language offers several libraries and frameworks, and all of them are ideal for machine learning and data analysis and manipulation. Although Python has a huge set of libraries and frameworks, the ones used for data science with time series forecasting include pytorch, keras, tensorflow, schikit-learn, statsmodels, scipy, numpy and pandas, to name a few.
R:
Another popular programming language among data scientists, R offers a set of functions and packages for machine learning, data manipulation, data visualization and data analysis. In case you don’t know, some of the most commonly used functions and packages may include arima, prophet, forecast, ggplot2, tidyr, and dplyr.
Spark:
This distributed computing system can help parallel processing of data. This framework offers Spark MLlib library for scalable ML algorithms in the field of data science. Besides, Spark’s Spark TS library offers algorithms for scalable time series analysis. Therefore, Spark is one of the best tools that you may want to learn to use if you want to shine in the world of data science.
Hadoop:
Like Spark, it’s another popular distributed computing system with distributed storage and processing of a large amount of data. This framework features HDFS, a distributed file system that helps store data. Another component is known as MapReduce, which is ideal for parallel data processing as a programming model.
Machine Learning:
Often abbreviated to ML, this is part of AI that allows the creation of complex algorithms for making predictions or decisions based on the learning from data. The good thing about ML is that it helps perform a number of tasks like feature extraction, anomaly detection, dimensionality reduction, regression, classification and clustering.
Seaborn:
This Python library allows you to create statistical graphics through high-level interfaces. You can use this library to visualize time series data and get a deeper insight into the patterns and trends.
Matplotlib:
Unlike Seaborn, this Python library features low-level interfaces to help create graphical plots. You can use this library to customize the style and look of the time series plots.
Airflow:
It’s a popular open-source system to help you make, schedule and monitor data pipeline workflows. The purpose of airflow is to automate the data science job execution and orchestration with respect to time series forecasting.
Facebook Prophet:
This open-source tool offers a robust method to create time series forecasts. The thing is that it employs a Bayesian approach for modelling the uncertainty, trend, and seasonality of time series data.
ARIMA variants:
The full form of ARIMA is Auto-Regressive Integrated Moving Average. Basically, ARIMA is a statistical model and offers a lot of variants in the form of modifications and extensions of the primary model like SARIMAX, ARIMAX, and SARIMA.
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Long story short, if you want to start your career in the world of data science, data science with time series forecasting is your best bet. Bangalore is one of the best cities to learn data science. Therefore, all you need to do is look for a good institute in Bangalore and get enrolled on a course.
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