4.9 out of 5 based on 4000 Students Rating
AI Tools used in Data Analytics
1. Microsoft Excel (Analyse Data/Flash Fill)
2. Business Intelligence with AI (Power BI/Tableau)
3. AI Enhanced Programming Libraries (PANDAS/NUMPY/PYTORCH)
4. ChatGPT (Explore Datasets, Clean Data via AI)
5. Grok AI
6. DeepSeek AI
7. Gemini (AI Tool for Data Analysis)
8. Copilot
• Definition and scope of data science
• Exploration of the importance and diverse applications of data science across various industries
• Examination of the historical background and evolutionary trajectory of data science
• Overview of basic statistical concepts
• Understanding to probability distributions
• Differentiation between descriptive & inferential statistics
• Introduction to hypothesis testing methodologies and significance levels
• Understanding Data Visualization, its tools & libraries such as Matplotlib, Seaborn, etc.
• Techniques for data visualization, distributions, relationships, and patterns
• Interpretation of visualizations to extract valuable insights from the data
• Understanding the basics of data mining and its importance in extracting valuable insights from massive datasets.
• Exploring the process of data mining and its applications in various industries.
• Discussing the challenges & ethical guidelines in data mining.
• Comprehension of the attributes and utility of lists and tuples
• Execution of operations to manipulate lists and tuples
• Utilization of list comprehensions for streamlined data manipulation
• Introduction to dictionaries and sets as primary data structures
• Introduction to machine learning & its algorithms
• Implementing supervised and unsupervised learning techniques
• Examination of data sources and categorization into structured and unstructured data
• Survey of diverse data collection methods
• Exploration of various data storage formats such as databases, spreadsheets, JSON, and CSV
• Deconstruction of the data science process into key stages
• Identification of the pivotal role of a data scientist at each stage of the lifecycle
• Illustration of the data science lifecycle
• Illustration of data cleaning & pre-processing techniques
• Strategies for handling missing values and outliers in datasets
• Introduction to feature engineering methods for creating new data attributes
• Overview of popular data science tools and platforms including Jupyter Notebook, RStudio, and Anaconda
• Introduction to version control systems such as Git for collaboration and project management
• Guidance on setting up a data science environment, including installation and configuration of necessary tools and libraries
• Introduction to clustering algorithms for grouping similar data points together.
• Exploring unsupervised learning algorithms such as k-means clustering and hierarchical clustering.
• Discussing methods for evaluating the quality of clustering results.
• Exploring machine learning algorithms for predictive analysis.
• Applying advanced techniques to analyze real-world datasets.
• Engaging in hands-on projects involving real-world data visualization tasks.
• Applying acquired skills & techniques to tackle data-centric challenges.
• Presenting project outcomes and insights to peers for constructive feedback and discussion.
• Getting familiar with big data and why it's important in today's world.
• Learning about the main features of big data: how much there is, how fast it comes, how varied it is, and how reliable it needs to be.
• Exploring the challenges and opportunities that come with working with big data.
• Discovering the different parts of the Hadoop ecosystem and what they do.
• Understanding how Hadoop's file system helps store lots of data across many machines.
• Recognizing the significance and practical applications of data analysis.
• Introducing fundamental concepts and principles essential for proficient data analysis.
• Surveying prevalent software and tools employed in the field of data analysis.
• Understanding R language syntax and structure
• Getting started with RStudio IDE
• Fundamentals of variables, data types, and operations in R
• Control structures: loops and conditions
• Exploring vectors, matrices, arrays, and data frames
• Manipulating and accessing different data structures
• Applying functions to perform operations on data structures
• Utilizing dplyr for data manipulation tasks
• Tidying data with tidyr: reshaping and transforming
• Filtering, selecting, arranging, and summarizing data efficiently
• Importing and exporting data from various sources
• Reading and writing data from/to databases
• Managing different file formats in R
• Advanced data manipulation techniques
• Working with time-series data and forecasting
• Introduction to NLP and text mining
• Integration of R with other tools for advanced analytics
• Implementing data cleaning methodologies to fix errors.
• Strategizing category wise data handling through encoding and transformation techniques.
• Understanding artificial intelligence.
• Exploring the history and evolution of artificial intelligence.
• Surveying the diverse applications of artificial intelligence across various industries.
• Discussing the ethical implications and societal impact of artificial intelligence.
• Introducing the fundamental principles of machine learning.
• Understanding the difference between supervised, unsupervised, and reinforcement learning.
• Exploring key machine learning algorithms such as linear regression, decision trees, and k-nearest neighbors.
• Understanding supervised learning concepts and objectives.
• Implementing regression algorithms for predicting continuous outcomes.
• Exploring classification algorithms for predicting categorical outcomes.
• Understanding unsupervised learning methodologies.
• Exploring clustering algorithms like K-means clustering and hierarchical clustering.
• Dimensionality reduction techniques.
• Applying unsupervised learning for data exploration & pattern recognition.
• Understanding and working with human language in computers.
• Discovering how NLP has evolved over time and where it's used today.
• Exploring how NLP helps in different fields like healthcare, finance, and customer service.
• Getting started with preparing text for analysis.
• Learning simple methods to break text into smaller parts, find root words, and fix common mistakes.
• Understanding why we remove certain words and punctuation from text and how we make spelling consistent.
• Diving into more advanced topics in NLP, like answering questions, having conversations, and understanding language better.
• Exploring new ideas and technologies in NLP, like big language models that learn from lots of text.
• Trying out what we've learned in practical projects and seeing how NLP can help solve real-world problems.
• Basic understanding of deep learning and neural networks.
• Investigating the historical context and evolution of deep learning.
• Exploring the diverse applications and significance of deep learning across various domains.
• Familiarizing with artificial neural networks (ANNs) and their architecture.
• Understanding neurons, layers, and activation functions.
• Delving into the mechanisms of feedforward and backpropagation algorithms employed in training ANNs.
• Surveying prominent deep learning frameworks such as TensorFlow and PyTorch.
• Hands-on engagement with constructing and training neural networks using these frameworks.
• Merits and limitations of different deep learning frameworks.
4.9 out of 5 based on 4000 Students Rating
The demand for a data analyst in the fast-paced world has become more pronounced for organizations. Now, organisations also realise the importance of data analysis to make better decisions to pursue a business successfully. The demand for data analysts in tech hub Delhi is surely increasing. A Data Analytics Course in Delhi might be the best course for someone who wants to start a well-rewarded career in data analytics. Data Analytics has generated the importance of data management where information has become a form of wealth employed by companies to earn a competitive edge. In this respect, data analysts facilitate insightful information for the success of the organisation. Additionally, addressing the metropolitan city. Delhi is a tech hub that has witnessed an upward trend in demand for data analytics professionals. Most organizations are investing heavily in advanced technologies; hence, there’s a need for expert data analysts who can help the organization with data for a good business. To enrol yourself in Data Analytics Course in Delhi, choose GICSEH, which is gaining popularity due to its ability to provide candidates with the knowledge and necessary tools to help them grab a successful career in Data Analytics.
Data Analytics is essential in today’s data-driven world. It allows organizations to extract meaningful insights from vast amounts of information, enabling smarter, faster, and more accurate decision-making. Whether it's understanding customer preferences, forecasting sales, or optimizing internal operations, data analytics helps improve efficiency and performance. Businesses that invest in analytics gain a competitive edge by responding to market trends and customer needs more effectively. In every industry from retail to healthcare data analytics is now a fundamental part of strategy, operations, and growth. Learning these skills today means preparing for tomorrow’s most in-demand careers.
Data analysts play an important role in businesses today. Thus, the core role of a data analyst is to collect, process, and present the data in a significant manner with useful information to be used in running a successful business. Data can also be used to make strategic decisions to outsmart the level of your competitors. Data informs concerning strategic decision-making. It also helps in improving operational efficiency, enhancing the experience of customers, and making an informed decision. From e-commerce, to finance, and even manufacturing, with all these technological advancements, every industry will now need data analysts. The future role of Data Analytics will continue to expand and stand out in generating informational strategies for business.
In today’s world the impact a data analyst plays is highly transformative. It empowers businesses, governments, and organizations to make decisions backed by evidence instead of intuition. In e-commerce, analytics personalizes customer experiences and boosts sales. In healthcare, it improves patient care by predicting disease outbreaks and treatment effectiveness. In finance, it prevents fraud and drives smarter investments. Even education, logistics, and sports are optimizing outcomes using analytics.
Data-driven insights lead to better resource allocation, cost savings, and strategic planning. With artificial intelligence and big data technologies advancing rapidly, the role of analytics continues to grow. It’s no longer a luxury—it’s a necessity. For professionals and students, mastering data analytics means unlocking high-paying, future-ready careers across industries.
Courses offered in the Data Analytics Training Institute is completely designed on the terms of requirements of this growing market. GICSEH offers full courses along with training to those who are interested in gaining experience in data analysis. Not only is the demand for a data analyst up, but it also offers high-paid jobs in the largest organisations along with multinational companies, financial institutions, and tech startups. The course includes data analytic training to help users gain hands-on experience with the tools and techniques available to combat real-world problems, including that of machine learning.
Comprehensive Learning with Real-World Exposure
Joining a Data Analytics Course in Delhi has numerous benefits for users who wish to have a fulfilling career. Such courses will give users comprehensive knowledge about Data Analytics principles, starting from how to collect data to the most advanced analytical techniques. Another benefit to pursuing studies in the Data Analytics Course in Delhi is the networking. A good institute will connect its students with industry leaders, and take them to various workshops, internships, and many more. So, GICSEH can be the best institute for anyone who wants to grab the competitive job market just by mastering data analytics.
Expert Mentorship, Tools Training & Placement Support
The Data Analytics Course at GICSEH doesn’t just provide technical education to you. The students have the opportunity to work on real-world projects using retail, healthcare and finance data sets. The job-oriented courses focuses on employable skills and market needs. The students get to walk into a occupation. The students have hands-on experience on industry-standard tools like Excel, SQL, Python, Tableau, Power BI, and the fundamentals of machine learning. Students functionality with tools is governed and mentored by certified trainers. The institutes' wide network allows consistent access to internship opportunities and related work experience with 100% placement support. Lab hours available 24x7 along with LMS support, students have a choice of offline, online, hybrid class schedules, and a recognized certification in the industry for data analytics, all of which meet the needs of the students.
Development of Soft Skills for Career Readiness
In addition to technical mastery, the course also emphasizes essential soft skills that make a real difference in the workplace. The learners are trained to communicate effectively and provide insight to both technical and non-technical types of audiences. Learners are encouraged to think critically and be creative problem-solvers in order to view business situations from different angles. They participate in team and individual projects, which improves their teamwork and collaboration. Learners are also trained to produce dashboards and presentations to provide visual stories through complex data. This is a unique tool and will expand their capability to provide data stories. Finally, they engage in time management training so they can handle more than one project and prepare for the responsibilities of a modern-day, data-driven professional role.
Let’s understand Data Analytics by what Data Analysts do. A data analyst collects, cleans, organizes, and interprets large volumes of raw data to uncover patterns, trends, and insights that help businesses make smarter decisions. Data analytics refers to the the exploitation of raw data, which we complete the process of cleaning, transforming, and modeling, to generate insights from the data that can guide decision making. Data analytics is a process that involves many tools and techniques to analyze large and complex datasets in order to extract relevant meaning in formats such as patterns, trends, and correlations. This field covers a wide array of methods, such as descriptive analytics, which summarizes and describes data; diagnostic analytics, which digs into the reasons behind past events; predictive analytics, which looks ahead to forecast future trends; and prescriptive analytics, which suggests actions based on the analysis results.
Organizations utilize data analytics to improve their decision-making, optimize operations, increase efficiency, and create a competitive advantage in many industries. Data analytics is a multidisciplinary field that integrates statistics, mathematics, computer science and domain expertise to extract insights from data.In learning the skills offered through the data analytics course in Delhi, you will master the ability to turn raw data into actionable intelligence and identify trends and patterns that can influence the future.
Descriptive Analytics: Discovering What Happened
Descriptive analytics helps to answer the question "What happened?"
It is a way of taking historical data and aggregating it in many different way to create charts and tables. Examples would include sales from last month, website visits for some period, or aggregate customer feedback. It allows businesses to understand what happened in the past and see any trends that occurred in that data.
Diagnostic Analytics: Finding Out Why
After knowing what happened, you can now ask "Why did it happen?"
Diagnostic analytics goes one step further. This kind of analytics looks for relationships and patterns, and uses that information to explain why one outcome occurred instead of a different outcome. If your website saw a significant decrease in traffic, for instance, one could use diagnostic analytic tools to determine if the decrease was because of slow loading speed, SEO changes in your market, or the performance of a marketing campaign.
Predictive Analytics: Forecasting Future Events
This is where we transition from understanding the data to framing insights within anticipatory context. Predictive analytics uses information from diagnostic analysis, applies statistical and machine learning models, and uses that output to explain: "What could happen next?"
Businesses utilize predictive analytics to forecast sales, predict customer churn, or anticipate demand patterns in the market which helps them stay ahead of their competition.
Prescriptive Analytics: Making the Best Decision
The most advanced type, prescriptive analytics, tells you: “What should we do now?”
It uses algorithms and data-driven simulations to recommend actions. Whether it’s optimizing a supply chain or personalizing customer offers, prescriptive analytics turns insight into strategy.
At GICSEH, our Data Analytics Training in Delhi equips you with practical knowledge of all four types of analytics this ensures you're not just learning tools, but mastering the thinking behind modern data science.
Relevance of Data Analytics Training in Delhi in 2025
As 2025 approaches, businesses are facing rapid digital transformation. Organizations of every shape and size are in a state of quickening evolution toward a digital era. Data has become the core of decision-making for start-ups and multi-national organizations alike. To keep pace with the competition, organizations are swapping their intuitive strategy for data-driven models to work more efficiently and with the goal of optimizing their customer's experience. As a result, we're seeing unprecedented demand for talent with a data analytics skill set in every sector imaginable such as finance, healthcare, advertising, logistics, retail and government.
With AI, machine learning, IoT, and automation influencing data volume and complexity in profound ways; employers are no longer solely looking for IT specialists. Companies want data literate individuals who can clean, process, analyze, and visualize data meaningfully. It has now become essential for any career that is thinking ahead to have foundational skills in key software (including Python, SQL, Excel, Tableau, and Power BI) and to combine those software skills with statistical understanding and critical thinking. A data analytics course can give students the foundations proven to help them to be more employable and better positioned for the future.
Delhi NCR is a tech-savvy region and is driving the huge demand for trained data analysts. Start-ups, MNCs, and even government organizations are investing heavily in their data science and analytics teams. By 2025, Data Analyst, Business Analyst, Data Scientist, BI Developer, and Analytics Consultant will be some of the fastest growing, and some of the highest-paying job roles in the marketplace, and in case you are interested to pursue a Data Analytics Course in Delhi with a reputed institute like GICSEH, you will gain exposure to practical training, real-world projects, and comprehensive placement support—hine to pursue an ever-relevant career today that is needed for tomorrow.
The Data Analytics Training in Delhi at GICSEH is designed for individuals who are ready to thrive in the age of data. Whether you're a student, a working professional, or someone looking for a career shift, this course is your gateway to a high-growth industry. It helps you build job-ready skills, improve decision-making abilities, and become more valuable in the workforce.
The Data Analytics Course at GICSEH is suitable for anyone no matter if you are new to the field, transitioning to a new career, or looking to enhance existing skills. Because this program is open to graduates of any background, including arts, commerce, and science, it allows a new graduate to come in with job-ready skills and do amazing work as a data analyst. For professionals with no background in analytics or data-centric work, it is an excellent course to complete as they transition to a new data/analytical-focused role. Data has become one of the highest-paid jobs for graduates, and a data role comes with job security that many other roles may not have.
If you are interested in performing work in data analytics as a new role for your career or a new role in your career path, even if the role does not always include "data analyst" in the title, it can be a great focus for your decision-making. Data is everywhere and is only becoming more prevalent in business. The analytics capabilities you will learn can allow you to become a highly sought-after applicant for any opportunity that includes a data component or, perhaps more importantly, advanced analytics for decision-making!
This program is also very relevant to entrepreneurs or business owners who want to make informed data-centered decisions for the growth of their companies. If you are a freelancer or consultant who works with clients in any area of strategy, marketing, and business intelligence, the ability to learn how to structure, analyze, and interpret data that clients can act on can add immediate value.
If you are a postgraduate student or researcher seeking to add details that are relevant to their studies or growing the importance of the academic qualifications they have obtained to develop skills to address practical questions in in-demand job areas, this course has great value.
Data analytics is widely recognized as an excellent approach to landing high-profile jobs in 2025 and beyond.
The demand for data analysts is surging across virtually every industry, from healthcare to finance to retail, as organizations increasingly rely on data-driven decision-making.
Driving factors for data analytic leading to impressive job profiles:
Strong job market growth in Delhi:
The data analyst job market in Delhi is strong, in alignment with global trends. This job demand is partially boosted by the exponential increase in data across areas like IT, finance, e-commerce, and healthcare, which has created a continuous demand for skilled data personnel to pull insights into the highly usable and actionable range. Therefore, jobs as data analyst are increasingly perceived as stable and future-proof job profiles in the Delhi region.
Good salaries in Delhi:
The average salary for a data analyst in Delhi is approximately ₹6.6 lakhs annually, but most earn somewhere around ₹4 lakhs to ₹10 lakhs a year.
A Fresh data analyst (entry-level) starts anywhere between ₹3 lakhs and ₹6 lakhs/year and a Mid-level data analyst (3-5 years' experience) salaries could be in a range of ₹6 lakhs and ₹12 lakhs.
Senior data analysts or those with specialized skills can expect salaries ranging from ₹12 lakhs to ₹18 lakhs or more, particularly in the top firms or niche industries.
In rare cases, and with considerable experience, total annual earnings may reach up to ₹17 lakhs among the top earners in Delhi.
These numbers suggest that organizations in Delhi highly value data analytics skills: compensation packages are on the rise as demand for skilled professionals continues to exceed the supply.
Career Progression: After starting as a data analyst, it is possible to move into more advanced roles, such as data scientist, analytics manager, or chief data officer, depending on skills and experience.
Transferable Skills across Industries: skills in data analytics are highly transferable and allow people to work in a wide range of industries and move into management or specialized technical roles.
Future-Proof Skills: Data analysts who are able to keep up with advances in AI, machine learning, and cloud technologies are always going to be in high demand and less likely to be automated out of their jobs.
The data analyst job market looks strong through 2025... a reasonable amount of expected salary growth and growing geographic opportunities appears to confirm that data analysis is a relevant and valuable career path".
To sum up, skills in data analytics open not only opportunities for employment but create possibilities for high-profile, future-proof roles.
“The data analyst job outlook for 2025 remains robust and promising... substantial salary growth and geographical diversification of opportunities suggest that data analysis remains a highly valuable career path”.
There are no hard and fast rules to join this course. Any individual with a graduation degree in arts, commerce, science or engineering can join the course. No prior coding or performing analytics is required, as we will start from fundamentals and end with advanced tools and techniques. You neither need prior coding/analytics experience, as the course starts with basic concepts and builds all the way to advanced tools and methods. As long as you are computer literate and willing to learn, you will do just fine in this course. The course is aimed at students, those looking for jobs, working professionals, and entrepreneurs who want to build a successful data-driven career.
Admission and Application Process at GICSEH
Overview
Global Institute of Cyber Security & Ethical Hacking (GICSEH) provides a simple and uncomplicated admissions process for all of its IT and non-IT courses. GICSEH offers a range of courses including Data Analytics, Cyber Security, Networking and many others. The aim of this process is to accommodate any level of student backgrounds and is simple enough to complete quickly.
Step by Step Process of Admission
Direct Admission
An open admission policy: Most of GICSEH programs are considered direct admission programs which means a prospective applicant may enroll to the course without writing entrance exams or pre-screening.
Eligibility: To be considered for admission applicants must typically complete their 12th standard (or higher secondary education).
Submission of Application
Online application: The student can apply to GICSEH by visiting the official website and selecting the course they wish to pursure.
Offline application: candidates can also come to the university campus and complete the application process there.
Choosing a Batch
Admission into batches may happen at any time during the month: New batches begin in the first or last week of every month - it gives students flexibility when commencing courses.
Most diploma courses are generally one year programs - short term courses - 2 to 4 weeks are also available.4. Payment of Fees
Course fees are based on the program, and for diploma courses, the range is typically ₹70,000 per year.
Additional expenses may include application and exam fees, as well as study materials.
Fees can be paid online or at the institute.
Confirmation and Enrollment
Students will receive a confirmation of their enrolment and course information when their application and payment have been processed.
Other Support
Counselling and guidance - GICSEH is available to help students select the course that is best for them and to help them understand their career options.
Placement - Students that have enrolled in the course will receive placement support with Career Services following completion of their course.
Contact for Admission
Website - you can visit the official GICSEH website to find the most up to date admission information and access to the online application.
Telephone - direct phone numbers are provided on the GICSEH website for inquiries, and personal assistance.
Eligibility Criteria for Data Analytics Institute in Delhi (GICSEH)
GICSEH (Global Institute of Cyber Security & Ethical Hacking) is offering a Data Analytics course in Delhi for individuals that want experience and knowledge in data-analysis roles. The eligibility requirements for the course are typically general eligibility and accessible for most applicants.
Common Eligibility Criteria
Educational Qualification:
The applicant must have completed at least 12th standard (higher secondary education) from a recognized board.
Interest in Data Analytics:
There is no restrictions on freshers, graduates, working professionals or those simply interested in starting a career in data analytics.
Basic Computer Skills:
While not a requirement, being familiar with the computer basics and working with data would be helpful.
Stream Restriction:
There is no stream restriction. Students coming from the Science, Commerce or Arts streams can all qualify. Having a stream in mathematics, statistics or computer science would be helpful.
Miscellaneous Information
No Age Restrictions:
The course does not have an age limit or age restriction to join the course.
No Prior Coding Knowledge Needed:
This course starts at the base level of learning, so applicants do not need prior coding knowledge or experience.
Practical Skills:
The curriculum focuses more on practical training, real projects in real situations, and industry-related tools.
Admission Process
Direct Enrolment:
Most candidates will apply directly on the website or on campus.
Counselling/Guidance for Students:
GICSEH also provides counselling to brief students about the course structure and career opportunities.
Course Benefits
Industry-Focused Curriculum
Allows students to build networks
Placement assistance
GICSEH’s Data Analytics course is designed for anyone who would like to enter the field of data analytics, with few academic restrictions and all training will be practical and job focused.
One-on-one support from trainers to ensure students can get through all topics and build their strengths.
Development of skills outside of academic courses
Focus on overall student development: soft skills; problem-solving; critical thinking skills to help develop student for varied IT roles - regardless of the specialisation.
Additional Benefits
Modern Infrastructure
Modern labs and equipment with the latest tools and technologies to create real-world learning experiences.
Exposure to Experts
Student will have the opportunity to meet industry professionals, take part in hackathons to work with real-world problems.
Variety of Courses
Over 100 courses available in IT or non-it for students, fresh, and working professionals regardless of their background.