Data Science Course in Bangalore

Different job roles of a Data Science Specialist

Data Scientist

A data scientist analyses corporate data to discover important insights. The data scientist converts the raw data into an analysis-ready format after the data has been collected. A data scientist applies statistics, mathematics, programming, science and machine learning techniques to discover meaningful insights from data. To guarantee uniformity, completeness, and accuracy, the data needs to be cleaned and checked. Before starting the data collection and analysis, the data scientist tackles the issue by presenting the appropriate questions and seeking knowledge. Data scientists assemble structured and unstructured data from a wide range of sources.

Data Analyst

Large amounts of data, such as those from customer surveys and sales statistics, must be analysed in order to unearth useful information. Data analysts collect and analyse data using specialised technologies to produce knowledge that aids in decision-making. They will react to inquiries about the data and look for patterns, trends, and irregularities. They need to be adept at manipulating and presenting data. Our Data Science training Institutes in Bangalore provide specialised tools to gather the needed data.

Software Engineer

A software engineer is a specialist in information technology who creates, develops, and maintains computer software for a business. They employ the concepts of software engineering, their technical expertise, and their creativity to assist in resolving new and persistent issues for a business. Software engineers analyse task deadlines and schedule work tasks. This can involve working with other software employees on challenging tasks, including updating or creating new software systems and testing and resolving any written code errors.

Data Science Lead

A data science lead is an important functional role with a wide variety of responsibilities within a company. They are in charge of managing the entire process of gathering, cleaning, and preparing data. They need to be familiar with current technologies and frameworks in order to handle complex business concerns.

NLP Engineer

A natural language processing engineer is responsible for developing cutting-edge NLP systems. They often have substantial training in computational linguistics and artificial intelligence. They are typically required to create clever apps employing data collected from texts. They may focus mostly on developing analytic solutions or on employing automation to generate new text.

Data Science Manager

The role of a data science manager is to assist the organisation in making use of data. They achieve this by working together with a team of engineers and data scientists that provide management with insightful direction and guidance so that they may make appropriate decisions. A data science manager oversees the whole project team. Our expert trainers of the Data Science Course in Bangalore help the students set deadlines, allocate needed resources, and assess results.

Business Intelligence Analysts

A business intelligence analyst does much of the same work as a data analyst. However, they use different methods to gather and analyse information. BI analysts often specialise in reporting and dashboarding.

Data Architects

A data architect designs data models, infrastructures, and processes for storing and processing information. He or she also develops solutions for managing and integrating data across various applications. They are highly skilled in database management and query languages.

Database Administrators

Database administrators manage and administer several types of databases. They design and implement database schemas and monitor performance and availability. Their primary responsibility is ensuring security.

Information Security Specialist

 An information security specialist monitors network traffic for sensitive data which could compromise a company’s security. These professionals develop policies and procedures that protect confidential client information.

Business Intelligence Consultants

A business intelligence consultant specialises in creating reports and visualisations based on data sets. They can create complex queries and dashboards based on data sets. Sometimes a business intelligence consultant creates custom solutions when no off-the-shelf product exists.

Information Retrieval Specialist

An Information retrieval expert helps find relevant information from vast stores of knowledge. In many cases, information retrieval specialists use natural language processing systems such as search engines or QnA techniques to extract information from documents. The term is used mainly in libraries and academic circles, though it has been adopted elsewhere.

Statisticians

Statisticians analyse datasets looking for patterns and trends. They study correlations between variables and produce statistical predictions.

Database Administrator

Database administrators maintain computerised information and ensure its integrity. They plan upgrades and backup systems, install databases, configure programs like ERP, and back up data.

Big Data Engineer

This role has emerged as a need because of the large amount of data being produced by consumers using mobile devices, social networks, web services, and cloud computing. Big data engineering involves developing tools to collect and store large amounts of unstructured data to perform real-time analytics.

ETL Developers

Enterprise transformation layer developers translate raw data into useful formats for decision-making. They may be asked to transform from one format to another in order to obtain results more readily understood. For example, an ETL developer may take data in comma-delimited text files, convert them into CSV files, and then load these files into a relational database where they become easier to manipulate and display.

Skills required to be a Data Scientist

Programming languages and database

When your profession entails completing tasks and producing insights, you must have a solid grasp of the programming language. As a result, working as a data science expert necessitates knowledge of a number of computer languages in order to manage data and employ various algorithms as necessary. Data scientists commonly use a few essential languages, and recruiters expect fluency in these languages. They are

• SQL
• R, 
• Python.

Apart from that, a few essential databases, such as MongoDB and MySQL, are required to gather data and ensure its accessibility when called. Data scientists primarily use Python and R programming to deliver the outcomes required by most firms, regardless of industry. Learn in-depth skills at Python Training in Bangalore to become a skilled data scientist. To gather numerical and statistical data, they offer frameworks and tools that are effective.

Statistics

A data scientist must have a strong knowledge of statistics and mathematics to perform tasks and deliver the appropriate outcomes. It's essential to be knowledgeable in Algebra, Probability, Geometry, Matrices etc., for a strong foundation in data science. 

Data Visualisation

Visualisations are an effective way to convey information and direct an investigation toward its goal. Data visualisation is one of the most crucial skills since it involves more than just summarising the findings; it also entails comprehending the data and becoming aware of its flaws. Concepts are always better represented visually since they are better known and understood. Several of the techniques for data visualisation include charts, maps, histograms, 2D/3D plots, etc.

Web Scraping

The process of web scraping is used to collect data and information from the internet. This data is often kept in a local file for future editing and analysis. Having knowledge of Web scraping is crucial for a data scientist. There are many applications for web scraping, notably in the field of data analytics. Companies that carry out market research employ scrapers to get data from social media and internet forums. Numerous companies also operate in contact scraping, which refers to the process of scanning the internet for contact information to be used for marketing.

Machine Learning with Artificial Intelligence

If you work for a firm that manages and utilises massive amounts of data and bases its decisions mostly on that data, machine learning might be a skill that employers are looking for. Machine learning is a branch of data science that helps model data and generate results in the same way that statistics and probability do. With the use of machine learning and AI concepts, one can develop various algorithms and prototypes while also handling massive data sets, such as data cleaning and resolving errors. Data Science includes algorithms that are essential to AI.

One needs to have a solid understanding of machine learning and artificial intelligence in order to combine tools and approaches in different logic and decision trees. You'll study the craft of data analysis and machine learning with the aid of our data science training in Bangalore. Any data scientist with these skill sets will be able to tackle and overcome complicated problems specifically designed for forecasting or selecting future goals. Those who possess these skills will surely distinguish themselves as competent professionals.

Big Data

Big Data is a large, expanding, and bundled collection of data. Due to its size and complexity, no traditional data management system can hold or process this data efficiently. Businesses can use big data to make decisions while also utilising outside intelligence. Those who have worked with big data before may be aware that there are a number of limits that make handling this much data impractical and that special tools and strategies are required to resolve these difficulties. The Data Science Course in Bangalore provides hands-on training in tools such as Spark, Hadoop, and KNIME.

Being able to access web searches and websites like Facebook and Twitter has allowed organisations to fine-tune their business strategy. Conventional customer feedback systems are being replaced by new systems developed utilising Big Data technologies. These innovative tools read and evaluate client input using big data.

Problem-solving skills

For one to succeed in the field of data science, one must have the ability to manage complexity. Being confident in one's ability to identify issues and devise creative solutions when necessary is essential. When attempting to develop any solution that would demand clarity in data science concepts, it may be challenging to break the challenges down into multiple components and systematically align them.

Being a data scientist has been a successful career choice during the last few years. In addition to the growing importance of data and the desire to improve it, there are a number of additional reasons that have increased the demand for data scientists in India. They include

• Since it is a more recent industry, employees in this industry face less competition.
• Currently, jobs in data science are some of the most lucrative ones.

The majority of transactions started happening online as Covid-19 spread across India. These processes generated a significant amount of data, which sped up the training of data scientists in India. Data science is a field that has recently experienced a spike in popularity, and there are currently numerous academies in Bangalore that provide professional data science courses. One such establishment that provides thorough Data Science Training in Bangalore is the FITA Academy.

Benefits of Data Science Certification Training in Bangalore at FITA Academy

• Acquire in-demand skills- Data science is a rapidly growing field, and businesses are looking for professionals with the skills to work with and analyse data. This data science training in Bangalore can give you the skills you need to compete in this field.
• Gain experience with real-world data- Data science certification courses often include hands-on exercises with real-world data sets. This experience can give you the practical experience you need to work with data in the real world.
• Get noticed by top companies- With so many people competing for only a few jobs, these data science certification programs help you stand out from the crowd. Companies that offer data science training will notice your qualification and hiring potential.
• Boost your career prospects- A data science certification can help you stand out from the competition and boost your career prospects. You’ll learn how to use different technologies such as R programming language and SQL. You can also take Excel, Python, Tableau, Hadoop, Machine Learning etc. Courses may come with certificates once completed.
• Earn a higher salary- Companies that offer a data science job will be more interested in hiring someone with training or experience in this area than someone without it. Companies that know you have data science training will pay you more money. In fact, many data scientists were hired on their education alone before becoming experienced enough to do the actual job.
• No coding required- The majority of data scientist jobs don't require any prior knowledge of programming languages like Java, C++, Python etc., which could make them an attractive option if you aren't sure if you want to become a programmer. Most people who are hired for these roles come from business backgrounds and have learned to interpret data through coursework or previous experience.
• Easy to enter- There are no prerequisites to taking a data science certification course; anyone can enrol. All one needs is basic computer literacy skills, including familiarity with popular operating systems like Windows and OS X. Some programs require familiarity with databases and some maths, but there is no set curriculum.
• Affordable- When compared to other forms of study, such as bachelor's degrees, data science programs cost significantly less. Certificates in this area can usually be earned at a fraction of the price of a bachelor's degree. However, it should be noted that the quality of certificate courses varies widely, so you might not get what you pay for.
• No special equipment is needed- Data scientists rely on standard computers while studying. They might use additional software packages if necessary, but nothing special (such as specialised hardware) is required.

Data Science is a problem-solving discipline that includes a variety of tools and approaches for obtaining information from data. It is a field that is constantly evolving. The Data Science Course in Bangalore at FITA Academy orients on practical sessions and self-paced study. The lectures taught by the faculty use the most current teaching software methodologies giving the students the liberty to interact with the trainers. The students will work with real-world data and industry-based projects to help them attain proficiency in this field. 

FITA Academy provides the Best Data Science Courses in Bangalore that assist students in realising their potential by giving them the necessary direction. Our trainers are experts with years of practical experience and training in data science. Our primary goal is to offer a student-centred and comfortable environment so they can develop with us and succeed in life.

FITA Academy courses are planned and designed by integrating the current industry trend and skills necessary to become an efficient and successful data scientist. The course entails six modules covering significant concepts of data science. The first module is about introduction to data science and Python for data analysis. The programming language of Python is essential to excel in this field. Moreover, the students will be introduced to the need for business analytics, the use of cases and different tools available for data science.

The second lesson is on R, which includes practice with if statements and loops like for, while, repeat, break, and next, as well as examples of R packages and operators. The third module focuses on data wrangling, data exploration, and R data structure. The students will learn about the process of importing and exporting data from an external source. Comprehensive training will be provided on the concepts of data exploratory analysis, R data structure, functions, and application knowledge. 

The fourth module of the course provides extensive training on predictive modelling linear regression. The trainers of FITA Academy will impart theoretical concepts and the practical application of data science. The sub-topics of the modules include linear regression, Bivariate Regression, multiple regression analysis and its correlations. The final modules of the course will impart the students with practical training on industry case studies, instances of machine learning usage, the process flow of machine learning, and the categories of machine learning.