Data analytics course that is relevant, meets industry demands and is recognized by the European Credit Transfer and Accumulation System (ECTS).
Students from diverse backgrounds (technical and non-technical) are welcome to do the PG Diploma in Data Analytics with us.
100% flexible blended form of learning. Learners can choose from online and offline options or a blend of both, whichever suits the schedule of students. We focus on giving hands-on learning with constant student guidance by experts in the industry.
The Data Analytics Course offered by us is curated by experts working in the industry who have years of experience in the same stream and provide the best education.
We offer Postgraduate in Data Analytics and it is available in two modules. We have a certificate program which is for 4 months and an elaborate diploma program with artificial intelligence tools for a year.
6 Months
Total hours: 1000+
Contact hours: 400
Live classes + Blended eLearning
MCQs, Assignments & Projects
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Aicampus is a leading training institute for professional IT courses. It is known for its data analytics courses. We have strategic partnerships with tech giants such as IBM and NASSCOM to craft a curriculum of excellence.
Who : The Data Analytics Certification program is designed for beginners, recent graduates, and in-between professionals looking to advance their careers. Our range of postgraduate diploma programs is designed for people who have a basic understanding of data analytics and want to advance into more experienced positions. After finishing the course successfully, students can select from a range of diploma programs that correspond with their favorite subjects
In over six months, students explore fundamental and advanced ideas in Data Analytics, AI, and Machine Learning. Learners here benefit from our dedication to self-paced learning, experienced mentorship, and extensive placement support.
WHY : The faculty provides all learners a great deal of assistance to successfully complete the coursework and start a rewarding career path. Aicampus has gained the trust of a sizable student body by fulfilling its promise to provide guided study and placement support—a feature that is neatly incorporated into the PG in Data Analytics.
The certification conferred by IABAC in collaboration with Aicampus carries equivalent significance globally compared to a traditional post-graduate program. Our faculty is made up of professionals from the industry who pay close attention to their pupils, have a thorough awareness of current trends, and keep up with the latest developments.
1500 hours of belnded learning
Total 5 terms; 11 months program
First 3 terms common with PG Certification
Last 2 terms focused on Applied AI Specialization
Learners will be introduced to their mentors, the modules they will be taught, and the overall structure of the course. In this term, base building will be focused on so that further advanced concerts can be taught.
Strategies for resolving issues in business.
Essential ideas in programming, statistics, and mathematics.
Expertise in data visualization with programs like Excel and PowerBI.
Sessions covering SQL data management and analysis in-depth.
In this term, learners will be made familiar with the programming language—Python. The relevance of Python in various industries will be discussed. Students will master this programming language for basic statistical analysis, utilizing it for marketing analytics, mitigating risks, and enhancing efficiency in diverse sectors such as e-commerce and retail.
Python is an open-source, freely attainable language that is easy to learn and essential for data analysis without requiring a high level of programming knowledge. Learn about Python packages, operators, data types, user-defined functions, object-oriented programming fundamentals, and more.
This segment focuses on enhancing data comprehension and facilitating subsequent data processing. Finding underlying data structures and going deeper into data sets are made possible with the help of EDA through interactive charts and other teaching tools.
TStudents study the components of statistical analysis: descriptive and inferential statistics. The module covers summarizing data using measures like mean, and median, and concluding statistical tests like t-tests. In addition to these main statistical techniques, students also learn associational, predictive, prescriptive, and causal analysis.
Students will learn about employing statistical techniques to forecast future behavior in the term's last module. Predictive modeling uses past and present data to create models that predict future results. It employs two main algorithms: linear regression for continuous outputs in regression problems and logistic regression for discrete outputs in classification problems. Students will acquire a thorough understanding of these techniques and Python model creation.
Accurately measure and forecast hazards with a variety of technologies. By correctly identifying and assessing risks, you can help businesses avoid potential disasters.
Improve the workings of an organization by understanding the data of the organization better. Data analytics helps improve productivity and efficiency in this industry.
Examine how data analytics are being used in real-time in a variety of businesses. Get practical experience in handling business difficulties, adjusting to demands unique to your industry, and developing large-scale risk mitigation models.
Learn more about customer behavior and improve your return on investment with data analytics tools and techniques. Develop your ability to evaluate marketing data, spot trends, and improve campaigns for long-term client involvement.
Put your theoretical knowledge to use here under expert mentorship during practice boot camps. You will be able to understand how strong your concepts are and what more you need to know to be ready for the job market.
This final term teaches hands-on practice, project assignments, the final assessment, and preparations for placement with mock interviews, CV building, etc providing a comprehensive conclusion to the data analyst training.
Learn to complete a data analytics project on your own.
Understanding the requirements of business.
Develop a problem-solving mindset.
Capstone project with a mentor to help you understand the workings of the domain better.
Resume building.
Mock interviews to prepare for actual ones.
Multiple doubt clarification sessions.
Mentorship.
Portfolio for projects
Learners get to understand and learn to use the in-demand data analytics tool. You will work with Excel, PowerBI, SQL Server on Cloud, Python, Jupyter Notebook, and GIT in this course.
Students pick up on multiple skills that can be majorly divided into two types. The technical skills they will pick up during the course and the decision-making skills that they learn with hands-on learning this course provides.
Core Python is a free and open-source programming language designed for use in data analysis procedures.
Microsoft Excel is a popular application for managing, organizing, and displaying data. It has powerful features like built-in pivot tables for effective data visualization.Large datasets can be easily imported, explored, cleaned, analyzed, and visualized with its help.
Tableau is a comprehensive data analytics platform that simplifies data preparation for analysis and facilitates the collaborative sharing of data insights. Its robust visual analysis capabilities are easily shareable across organizations.
Power BI is a cloud-based analytical application that helps with data extraction and visualization by offering rapid insights into data. By consolidating multiple sources, it offers a comprehensive view of an organization's assets.
JIRA is an essential tool for business analytics since it evaluates team performance and produces comprehensive reports with beautiful visuals. Particularly useful in operational analytics, JIRA can also function as a database.
Microsoft PowerPoint is essential for data visualization, especially for presenting information to non-technical audiences. It provides a way to coherently express data insights. Alongside other tools in the MS Office suite, it forms part of a comprehensive analytical suite.
Azure Analysis Services delivers cloud-based enterprise-grade data models. Employ sophisticated mashup and modeling functionalities to aggregate, clean, and quantify data from several sources while maintaining data security in a tabular semantic data model.
Our PG program in data analytics ensures that students are well-versed in decision making as communicating results and conclusions to various executives is crucial for a data analyst to succeed. As a data analyst, possessing a comprehensive, 360-degree view of a situation is crucial.
Machine learning is everywhere and in everything. Businesses rely on machine learning to increase sales, lower costs, improve customer engagement, and design tailored advertisements. Machine learning is widely adopted in finance, healthcare, retail, and transportation. A data scientist unfamiliar with machine learning models and libraries will be in deep waters regarding career growth. Even if a data scientist has the skills necessary to collect and clean data, without machine learning, they won’t be able to create accurate models. Therefore, all data scientists need to understand machine learning techniques and concepts strongly.
Data visualization is another critical skill for data scientists. When communicating data to others, a bar graph or pie chart is much easier to understand than a table full of numbers. Data visualization is essential with Big Data. It may be possible to store and process all the data you need, but if you can’t make sense of it, there’s no point in collecting it in the first place. With data visualization, you can transform large amounts of data into a visual format that allows people to understand it more efficiently and make it more accessible. This is particularly important when it comes to data-driven decision-making.
As businesses continue investing in AI technologies, a new sub-discipline has emerged — robotics. Robotics, in general, is used to control and automate physical devices, such as autonomous vehicles. In the field of Data Analytics, though, it’s used to automate and manage analytical processes. For example, a data scientist might use robotics to create and deploy a model across a fleet of servers. This can help businesses scale their analytical processes to meet increased demand. For a lucrative career in Data Analytics , it’s a good idea to have a basic understanding of robotics and AI. After all, most businesses that use AI technologies are also investing in robotics to help scale these processes. Therefore, data scientists need at least a basic understanding of their technologies.
Data analysis is reviewing data to find insights and draw conclusions. Even if they’re not creating models, they must conduct data analysis as part of their daily processes. When performing data analysis, it is essential to identify patterns and trends in the data. This enables data scientists to draw meaningful conclusions about their data and communicate these results to others in the organization. If a data scientist isn’t skilled in data analysis, it can be hard to understand their data, let alone communicate it to others.
Data scientists need to understand how data is stored and processed from start to finish. This includes everything, from how data is collected and processed to how organizations store it. This is particularly important when businesses are shifting towards cloud storage. Data scientists must also have clarity on how their data is processed, including the tools and technologies used to process it. They can use this information to find ways to shorten their processing times and use their resources more efficiently.
The PG program in Data Analytics is designed for fresh graduates and early-stage professionals interested in starting or transitioning their career to Data Analytics.
Blend of online and classroom
Includes mentor support
Globally accredited recognition
High job-oriented with an industry-first approach
Scholarships and EMI payment options are available
Compact and industry-relevant post-graduate course curriculums
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PG Certificate in Data Analytics |
PG Diploma in Data Analytics |
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Anyone from maths, finance, business management, engineering can opt for this course |
You must have a bachelor's degree or complete PG Certification in Data Analytics course to enroll |
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PG Certificate in Data Analytics |
PG Diploma in Data Analytics |
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Admission / Application Process |
Online application directly through
Ai campus |
Online application, followed by profile screening and entrance test. Finally,
there will be an interview to select candidates |
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Course Fees |
INR 85,000 + GST |
INR 1,48,000 + GST |
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Scholarships |
Upto 18,000* |
Upto INR 40,000* |
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Financial Support |
0% Interest EMI available. Contact team for details. |
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* Scholarships on the total fee* for the eligible candidates.
Let us dive into the industry data analytics covers, what job roles you can apply for and what is the scope of data analytics, now and in the future.
We’ll start by sharing the sectors in which data analytics is used.
Telecom
Retail/eCommerce
Manufacturing
Healthcare
BFSI (Finance and Insurance)
Hospitality
As a data analyst, your role involves:
Collecting data from various sources and organizing it sequentially.
Data processing and cleaning, missing value handling, error correction, and undesirable information removal.
Proficiency in statistical tools like Python or SaS for data interpretation.
Building precise prediction models, managing and optimizing data in accordance with future and present market or seasonal trends.
Crafting detailed reports that are visually enriched and easily understandable.
Identifying security breaches, and potential threats, and facilitating organizational responses.
There is an increasing need for data analytics services and training. The scope can be seen according to reports, that there will be about 250,000 employment opportunities for data analysts in 2023 alone. IBM forecasted a total of 350,000 jobs in data science and analytics by the same year. This is high time to enroll in a genuine PG Program in Data Analytics and by being on time you can achieve more at a faster pace.
Enrolling in a well-structured data analytics course can set you on the path to becoming a successful data analyst across various fields. In the last decade, there has been a significant surge in demand for data specialists across different industries, making it imperative to acquire training in data analytics to stay competitive. The field of data science offers profit to the ones in it and is hence cut-throat. If you have the backing of a sound data analytics course it gives you an edge over your other contemporaries.
Whether it's analyzing a sports event or detecting early-stage cancer, data analysis plays a pivotal role in diverse domains. With the help of data analysis from healthcare to technology everything has become more efficient. The field of data analytics has continuously expanded since its inception. Every task, process, or even the smallest internet-connected device generates data that can be transformed into invaluable insights. This newfound significance of data has exponentially increased the relevance of analytics and data science in India. It is a booming field and a reputable data analytics certification course in India can give your career a strong head start in the industry.
Data analytics is a narrow niche of the data science field. Data analytics focuses on collecting data, cleaning the data, and organizing it, as well as descriptive and predictive data analysis. A data science training course, on the other hand, leans on machine learning algorithms for solutions. It teaches you how to identify patterns in data and formulate relevant questions.
Both data science and data analytics careers offer various opportunities. For example, the Business Analytics 360 course can guide you in starting from scratch to become a business analyst. If you want to deepen your understanding of algorithms and predictive modeling, a machine learning course can be beneficial.
Your choice of course should be influenced by your experience and knowledge, and keeping in mind what stream you aim to work in after completing the course. You will get all this guidance from expert mentors at Ai Campus. Ai Campus provides top-notch data analytics education in Bangalore, Noida, and Delhi for each of these career paths.
The path to a career transition in data analytics can vary significantly due to the broad nature of the field. It depends on the particular job you take up, the course you did, and the organization you are working for. However, we can draw insights from real-world experiences shared by our alumni. You can verify their journeys by checking their profiles on LinkedIn.
An inspiring example is of a history graduate who became a data analyst at Air India. Starting with advanced Excel skills, our wonderful student earned certifications in various analytics technologies. Despite lacking a computer science background, attributes some of his success to Ai Campus for providing him with precisely what he needed to make this remarkable career shift.
This example is just a glimpse of the many success stories in our alumni network, demonstrating that individuals from diverse backgrounds can successfully transition into data science. It underscores the fact that active professionals can obtain a data analytics certification with a bit of extra effort and achieve their career goals.
Ai Campus was established in 2011 and aims to provide a comprehensive array of data science training programs for IT/ITES working professionals. While many organizations share a similar mission, Ai Campus has earned a reputable status over the past decade through its distinctive approach. We aim to give a fresh learning start to working professionals in multiple streams like data science, data analytics, artificial intelligence, etc.
The core mission of Ai Campus is to enable the youth of India to harness future opportunities effectively and take the potential streams by their horns. Ai Campus is recognized as the top data science institute in India by Analytics India Magazine and stands out as a leader in the field.
When deciding a data analytics program for yourself there are multiple intersections of your future that you need to keep in mind. One cannot just go with a trendy or popular course because it might seem great but however, it might not cater to your needs. It's important to clarify a few points before addressing this question effectively. The first question to answer is about your specific goals. Have you considered potential career paths, and are you seeking training for a particular country or region? Addressing these aspects will help tailor the recommendation to your circumstances.
That said, many beginners often opt for the Data Science 360 course and the Business Analytics 360 course. You can find a comprehensive list of certification courses on our website for further exploration. You can have detailed discussions with our mentors at Ai Campus to understand each course. This will help you know what our courses offer and then come to a worthwhile decision.
Ultimately, the key is to choose a course that aligns with your professional objectives and brings you closer to your desired career or job. Data science and analytics are intricate fields, and the experienced instructors and mentors at Ai Campus are well-equipped to help you navigate through them, drawing from their extensive industry expertise.
It is definitely possible for non-programmers to make a successful career change and work in data analytics. The main question is how does one do that?
There are multiple roles in the field of data analytics that do not require coding knowledge. Their roles are those of data analytics project manager, data analytics consultant, data visualization specialist, and technical writer for data analytics software. Nevertheless, I understand that this might not be the answer you were expecting. It is perfectly viable to pick up coding at any point in life and use it to do better at your job.
In response to question 3, you can read about how a history graduate used Python to transition into a data analyst role.
For individuals without programming experience, Ai Campus offers the Data Analytics 360 course. This course is for people who have not ventured into coding before as data analytics and it’s tools are taught from scratch serving as an essential gateway to the field. This comprehensive program takes you through a three-part journey. You will first gain proficiency in SQL and advanced Excel, followed by learning R, Python, and the fundamentals of machine learning and predictive modeling after grasping the "building blocks of Data Analytics." Upon completing this course, you will be awarded dual certification from IBM and Ai Campus, along with a placement guarantee.
The Analytics Edge course primarily aims to prepare working professionals for careers in business intelligence, business analytics, and data analytics. This program is widely recognized as the most practical data analytics training available in India, catering to professionals seeking a comprehensive understanding of data analysis.
Here's a summary of what you will gain from this data analytics course. This analytics edge course is available on-site in Gurgaon, Bangalore, and Delhi:
Proficiency in managing relational database management systems.
A solid command of structured query language (SQL).
Competency in data visualization using Tableau and R.
Advanced Excel skills.
Entry-level skills in data science.
This course is designed to take you from a novice level to a versatile analytics professional, equipping you with the knowledge and skills needed to excel in a variety of analytics roles.
Yes! Ai Campus offers the best support available to all our learners. We aim to make the process as accessible and approachable as possible.