blog

What is Data Analytics? At its core, data analytics is the science that focuses on analyzing raw data to derive conclusions and insights that are otherwise not apparent. This involves a series of steps and techniques, which I’ve outlined below to give you a clearer understanding: Analyzing Raw Data: The primary goal is to make sense of vast amounts of data, turning it into useful information. Automated Processes and Algorithms: These are employed to make data analysis accessible and interpretable by humans. Application Across Industries: From optimizing business performance to making informed decisions, data analytics plays a pivotal role in various sectors. The journey of data analytics begins with identifying the data requirements and proceeds through collecting, organizing, and cleaning the data before any analysis is conducted. This multidisciplinary field draws on math, statistics, and computer science to uncover insights from data sets. Moreover, it encompasses a broad spectrum of processes beyond mere analysis, such as data science and data engineering, which are crucial for theorizing, forecasting, and building robust data systems. Understanding these foundational elements of data analytics not only demystifies the process but also highlights its significance in today’s data-driven world. Why Data Analytics is Important? In today’s rapidly evolving digital landscape, the significance of data analytics cannot be overstated. Here’s why: Informed Decision-Making: At the heart of data analytics is its ability to empower organizations with evidence-based decision-making. This moves businesses away from intuition or guesswork towards concrete, data-driven strategies. Competitive Advantage and Efficiency: Companies leveraging data analytics gain a competitive edge by making faster, more informed changes. This not only increases revenue but also reduces costs and fosters innovation, thereby optimizing overall performance and efficiency. Understanding and Anticipation: Data analytics tools provide invaluable insights into customer trends and satisfaction. This enables businesses to not only understand current consumer behavior but also anticipate future needs, leading to the creation of more targeted marketing strategies and product improvements. The global market’s growing reliance on big data and analytics, projected to reach $684.12 billion by 2030, underscores the critical role of data analytics across sectors. Whether it’s streamlining operations, enhancing customer experiences, or driving financial performance, the benefits of data analytics are manifold and indispensable in today’s business environment. Data analytics: Key concepts Delving into the heart of data analytics, it’s essential to grasp the variety of concepts that form the backbone of this field. Here are some of the key ideas: Types of Data Analytics: Descriptive Analytics: Focuses on summarizing historical data to identify trends and patterns. Diagnostic Analytics: Digs deeper into data to find causes and reasons. Predictive Analytics: Utilizes historical data to forecast future outcomes. Prescriptive Analytics: Suggests actions to achieve desired outcomes based on predictions. Core Process of Data Analytics: Identifying the question Collecting raw data Cleaning data to remove inaccuracies Analyzing the data Interpreting the results to make informed decisions. Key Techniques and Tools: Data Mining: Unearthing patterns and relationships in large datasets. Statistical Analysis: Drawing inferences and making decisions. Exploratory Data Analysis (EDA):Understanding data’s structure and characteristics. Predictive Modeling: Building models for future outcome prediction. Natural Language Processing (NLP): Facilitating human-computer interaction. Business Intelligence (BI) Tools: Extracting actionable insights from raw data. By understanding these foundational elements, individuals can better navigate the complex landscape of data analytics, leading to more strategic decisions in both business and research contexts. Data analytics skills To excel in data analytics, it’s essential to master a blend of technical and soft skills. Here’s a breakdown: Technical Skills: Structured Query Language (SQL) and NoSQL for database management. Statistical Programming using languages like R, Python, and MATLAB. Data Visualization tools such as Tableau, Power BI, and Microsoft Excel to represent data comprehensively. Machine Learning techniques including supervised and unsupervised learning, and natural language processing (NLP). Big Data Technologies like Hadoop and Spark for handling large datasets. Soft Skills: Critical Thinking and Problem-Solving to analyze data and draw conclusions. Communication Skills for effective data storytelling and presenting findings to both technical and non-technical audiences. Attention to Detail to ensure accuracy in data analysis and interpretation. Additional Skills: Data Management and Cleaning to prepare data for analysis. Statistical Analysis including descriptive, inferential, and hypothesis testing. Domain Knowledge to understand the context of the data and its implications. These skills are foundational for anyone looking to pursue a career in data analytics or enhance their capabilities in the field. Data analytics jobs Exploring the landscape of data analytics jobs reveals a dynamic and lucrative field. Here’s a snapshot of what to expect: High Demand and Competitive Salaries: With an estimated growth of 23% between 2022 and 2032, data analytics roles are not only expanding rapidly but also offer salaries well above the average, at around $85,720 annually. This growth, however, is accompanied by concerns over a talent shortage, emphasizing the need for skilled professionals. Diverse Roles Across Industries: Data analytics professionals can find themselves in a variety of roles, such as: Data Analyst Data Scientist Business Analyst Marketing Analyst Financial Analyst These positions involve tasks ranging from dissecting vast datasets and uncovering hidden patterns to translating numbers into actionable information for decision-making. Evolving Career Paths with Lucrative Salaries: The career trajectory in data analytics is not just limited to traditional roles. With the right skill set, professionals can transition to higher positions like Analytics Manager or Chief Data Officer, with salaries ranging from $61,807 for junior analysts to $183,481 for CDOs. The demand for these roles is reflected in the average salaries, which vary by role and location but consistently offer rewarding compensation . This overview underscores the promising prospects and financial benefits of pursuing a career in data analytics, making it a compelling field for those interested in leveraging data to drive decisions and strategies. What is big data analytics? Big data analytics is a transformative process designed to handle the complexities of massive datasets. It’s fascinating how it employs a variety of tools and techniques to reveal hidden patterns, trends, and correlations that inform strategic decisions: Core Process Collecting Data:

If you want to pursue an exciting and challenging career, you might consider enrolling in one of the top data science institutes in Thane. The basic purpose of statistics is to identify patterns and trends and derive conclusions from them. Top 5 Data Science Institutes in Thane Data Science, on the other hand, necessitates more mathematics and a comprehension of algorithmic processes, as well as computer programming. It combines the art of designing tables and charts with the science of predicting and analyzing data sets. If you want to become an expert, you should attend the best data science courses in India. What does it mean by Data Science? Data science training is an essential introduction to the field, with an emphasis on presentations, and you can learn more about it at these top data science institutes in Thane, Maharastra. Our trainers teach students the fundamental software used in computers and illustrate how algorithms and programs work. The tools will then be demonstrated using numerous examples in the form of extended demonstrations, lectures, and case studies. Although this may appear dull and uninteresting, it is where a career in this industry might begin. Become an expert Data Scientist with Top Data Science Courses If you’re looking to be a data scientist, then a course is the perfect answer. It is the very first step to begin your path as a professional in the field. Many prominent universities and colleges provide these sessions in top data science institutions in Thane to expose the subject so that future students can make a choice to pursue a certain career path based on the information they are given. A data science class at top data science institutes in Navi Mumbai will provide an overview of the data science process. The course will cover the foundations such as sample procedures and theories development. You will also be provided an overview of the process of implementation and the examination of scientific approaches. The goal for the Data Science course is to impart entire knowledge of data processing and managing with these top data science institutes in Thane. Courses in data science are provided at numerous technical and community colleges, as well as vocational schools. The benefit of course is that you’ll receive individual attention, with the top industry specialist having tremendous expertise. You are allowed to pick at any point in time whether you are ready to take an Intro to Computer Science class or enroll in a comprehensive independent course. Many students gain the skills needed to become an analyst of data fast in this class in data science. If you are interested in getting a master or post graduation degree in this profession then you must study this field with these top data science institutes in Thane, Maharastra. It is vital to choose your major after finishing a biology, chemistry and Physics major. The coursework required to complete the curriculum at the level of a Bachelor of Science degree are frequently covered in these classes in addition. In general, data sciences and degrees in computer science explore issues like statistics, computer science optimization, and computer vision. There are various certificates in data science that are offered in Rise Institute, Mumbai. Many of them are accredited and part of a larger curriculum but one isn’t. This program at Rise Institute in Mumbai offers an entire, full-time data science program that prepares students to work in the domains of data analysis, quantitative methodologies, and programmers. In these data science institutes in Mumbai, Maharashtra, students are eligible to pursue a credential in applied research. They must earn an associate’s level degree before applying to the program. List of Top 5 Data Science Institutes in Thane 1. Rise Institute Rise Institute, a data science training centre that has been rewarded with many accolades and recently earned best emerging academy of the year, offers advanced programs in the domain of data science to aid students in getting information on the subject they would like to follow. They also provide online courses to those wishing to become a top data scientist. With top-quality facilities for training, and high-end approach, our teachers delivers the best data science courses in Thane. Training to customize Data Science training, Rise Institute was formed in the year 2016, with Ashish Barde who is an IT specialist with knowledge in data analytics and data science to help people who are aspiring acquire the most effective and relevant industry training. As the leading data science institutes in Thane, our trainers also assist them in getting an advantage that will allow them to develop fantastic reputations with companies. How do you start in your desire to increase your technical abilities? You’ve come to the correct site. Since 2016, we have offered more than 10 thousand plus certified students across the country in various courses including Python, SQL, Data Analytics, Data Science, Artificial Intelligence, Machine Learning, among others. That encourages them to continue their professional and personal development? We are constantly curious to know how much our students have benefited from their education and how they can make their future bright with the finest data science institutes in Thane. We provide the doors of corporate to our students and Job seekers, as well as professionals and small-scale business owners. Rise Institute aspires to deliver an increase in professionalism and, subsequently growing our popularity with the different business houses. We are a leader on the internet, not an admirer who has a universal appeal. Rise Institute encourages, supports students’ skills and performance by giving the greatest training programs that help you become the best that you could be in online learning. Our mission is to deliver top quality materials, education, and student services to satisfy the real expectations of the internet market. Online Training We Are Global Skilled Faculties Highest Rated The major purpose of the greatest data science institutes in Thane is to incorporate computers into people from all fields including students, professionals, employees, Business chiefs as well as Housewives. We aspire to deliver

Introduction: In today’s digital age, data science has emerged as a crucial field driving innovation, efficiency, and decision-making across various industries. Whether you’re a seasoned professional or a novice enthusiast, navigating the vast landscape of data science can be overwhelming without a clear roadmap. In this guide, we’ll provide you with a comprehensive data science roadmap, equipping you with the essential knowledge and skills to embark on this transformative journey. Chapter 1: Understanding Data Science To embark on your data science journey, it’s crucial to first grasp the fundamentals of this dynamic field. Data science revolves around extracting insights and knowledge from structured and unstructured data using various techniques such as machine learning, statistical analysis, and data visualization. By understanding the core concepts of data science, you lay a solid foundation for your learning path. Chapter 2: Essential Skills for Data Science Mastering data science requires a multifaceted skill set that seamlessly integrates technical prowess with analytical acumen and problem-solving finesse. The data science roadmap delineates the trajectory towards proficiency in this field, emphasizing the acquisition of essential competencies. Central to this roadmap is the cultivation of expertise in programming languages such as Python and R, pivotal tools for data manipulation and statistical analysis. Mastery of these languages forms the cornerstone of proficiency in data science, enabling practitioners to navigate complex datasets and extract meaningful insights. Moreover, familiarity with machine learning algorithms constitutes another crucial waypoint on the data science roadmap. As the backbone of predictive modeling and pattern recognition, understanding these algorithms is paramount for leveraging the full potential of data science techniques. Whether it’s classification, regression, or clustering, a comprehensive grasp of machine learning algorithms empowers data scientists to derive actionable intelligence from raw data. In addition to technical skills, effective communication and collaboration represent integral components of the data science roadmap. As data science projects often involve interdisciplinary teams and stakeholders with diverse backgrounds, the ability to convey insights concisely and collaborate seamlessly is indispensable. Data scientists must articulate their findings in a manner comprehensible to non-technical stakeholders, bridging the gap between data analysis and actionable decision-making. Furthermore, the data science roadmap underscores the importance of continuous learning and professional development. Given the rapid evolution of technology and methodologies in this field, staying abreast of emerging trends and best practices is imperative for remaining competitive. Engaging in ongoing education, whether through online courses, workshops, or industry conferences, equips data scientists with the latest tools and techniques to tackle new challenges and opportunities. Ultimately, excelling in data science requires a strategic approach guided by the data science roadmap. By systematically honing technical skills, fostering effective communication, and embracing lifelong learning, aspiring data scientists can navigate the complexities of this dynamic field with confidence and proficiency. As they progress along this roadmap, they not only enhance their individual capabilities but also contribute to the broader advancement of data science as a transformative force in the digital era. Chapter 3: Learning Resources and Tools The expansive universe of data science is brimming with an abundance of learning resources and tools meticulously crafted to facilitate your journey along the data science roadmap. In this digital age, platforms such as Coursera, Udacity, and edX emerge as beacons of knowledge, offering a plethora of meticulously curated courses tailored to every milestone along the data science roadmap. From foundational principles to intricate concepts encompassing advanced machine learning algorithms, these platforms serve as indispensable allies in your quest for mastery. Furthermore, the landscape of data science is enriched by a myriad of open-source tools, each a potent instrument in the hands of the aspiring data scientist. Tools like Jupyter Notebooks, Pandas, and TensorFlow constitute the bedrock upon which practical experience is cultivated, providing a hands-on approach to data analysis and visualization. With these tools at your disposal, you embark on a journey of discovery, traversing the data science roadmap with confidence and clarity. Embracing the data science roadmap entails a continuous quest for knowledge and proficiency, and these platforms and tools stand as steadfast companions in your pursuit. As you navigate the intricate pathways of data science, each resource becomes a guiding light, illuminating the way forward and empowering you to surmount obstacles with ease. Whether you’re delving into the intricacies of statistical analysis or delving deep into the realm of predictive modeling, these resources equip you with the skills and insights necessary to thrive in the dynamic landscape of data science. Moreover, these learning resources serve as conduits for staying abreast of the latest trends and developments within the field of data science. As the landscape evolves and new methodologies emerge, these platforms act as vanguards of innovation, offering cutting-edge courses and modules designed to keep you ahead of the curve. Through continuous learning and exploration, you remain poised to embrace the ever-changing landscape of data science, armed with the knowledge and tools to adapt and excel. In essence, the world of data science is a vibrant ecosystem teeming with opportunities for growth and discovery. By leveraging the wealth of learning resources and tools available, you embark on a transformative journey along the data science roadmap, charting a course towards mastery and success. With each step forward, you deepen your understanding, refine your skills, and expand your horizons, ultimately emerging as a proficient and accomplished data scientist ready to tackle the challenges of tomorrow. Chapter 4: Building a Portfolio As you navigate your data science roadmap, one crucial milestone stands out: building a robust portfolio. This portfolio serves as a showcase, spotlighting your skills and expertise to prospective employers. It’s not just a mere collection of projects; it’s a testament to your proficiency in solving intricate problems through data science methodologies. With each project meticulously crafted and curated, you add layers of depth to your portfolio, bolstering your credibility as a data scientist. But how do you go about constructing this vital tool on platforms like Naukri, LinkedIn, or others? Let’s dive into the intricacies of crafting compelling job descriptions and resumes tailored for these platforms. When

Data Science vs Data Analytics: The Expert Comparison 2024 Introduction In the ever-evolving landscape of technology, two powerhouse terms that often find themselves intertwined yet hold distinct significance are “Data Science” and “Data Analytics.” While both revolve around the utilization of data to derive insights, their methodologies, objectives, and applications diverge significantly. In this comprehensive guide, we unravel the intricate disparities between data science and data analytics, shedding light on their unique attributes and the pivotal roles they play in driving organizational success. Understanding Data Science In today’s digital age, the terms “Data Science” vs “Data Analytics” are often used interchangeably, leading to confusion about their distinct roles and functionalities. While both fields deal with data and aim to extract valuable insights, they have nuanced differences that are crucial to understand. Data science can be perceived as the multidisciplinary domain that encompasses various techniques, algorithms, and tools to extract meaningful insights and knowledge from structured and unstructured data. At its core, data science integrates elements of statistics, mathematics, computer science, and domain expertise to uncover hidden patterns, trends, and correlations within datasets. The overarching objective of data science is to leverage these insights to inform decision-making, predict future outcomes, and drive innovation across diverse industries. On the other hand, data analytics focuses more on the analysis of data to identify trends, patterns, and metrics that can be used to optimize processes and make informed business decisions. While data science involves a broader scope, including data collection, cleaning, analysis, and interpretation, data analytics tends to concentrate on analyzing past data to understand current trends and make predictions for the future. One way to distinguish between data science vs data analytics is to think of data science as the foundation that encompasses various techniques and methodologies, including data analytics, machine learning, artificial intelligence, and big data analytics. Data analytics, on the other hand, is a subset of data science, focusing primarily on analyzing data to derive insights and make data-driven decisions. In practice, data scientists often work on the entire data lifecycle, from data collection and preprocessing to analysis, modeling, and interpretation. They utilize a wide range of tools and techniques, such as statistical analysis, machine learning algorithms, data visualization, and predictive modeling, to extract actionable insights from data. In contrast, data analysts typically focus on analyzing data using statistical methods, SQL queries, and data visualization tools to generate reports, dashboards, and visualizations that help businesses understand their data better and make informed decisions. While data scientists are more involved in developing predictive models and machine learning algorithms, data analysts specialize in descriptive analytics, summarizing historical data to provide insights into past performance and trends. Despite these differences, both data science and data analytics play critical roles in today’s data-driven world. Organizations across industries rely on data scientists and data analysts to unlock the value of their data, gain a competitive edge, and drive strategic decision-making. Whether it’s optimizing marketing campaigns, improving customer experience, or predicting market trends, data science and data analytics are indispensable tools for driving organizational success. In conclusion, while data science and data analytics are closely related fields, they have distinct roles and functionalities within the broader spectrum of data analysis. Understanding the differences between these two disciplines is essential for organizations looking to harness the full potential of their data and stay ahead in today’s competitive business landscape.        Difference between data science vs data analytics in table form: Data Science Data Analytics Skillsets include- Data Modelling Predictive Analytics Advanced Statistics Engineering Programming Skillsets include- BI Tools Statistics SQL Programming  Visualization Tools The scope is large scale. The scope is small scale. Explore and uncover new questions and their answers. Achieve your objectives by leveraging available data and implementing the right actions. Key Components of Data Science: Data Collection and Cleaning: The initial phase of any data science project involves gathering relevant datasets from disparate sources and cleansing them to ensure accuracy and consistency. Exploratory Data Analysis (EDA): Through EDA, data scientists aim to understand the underlying structure of the data, identify outliers, and discern meaningful patterns that can guide subsequent analysis. Machine Learning and Predictive Modeling: Machine learning algorithms play a pivotal role in data science, facilitating predictive modeling, classification, clustering, and anomaly detection tasks. Data Visualization: Communicating insights effectively is crucial in data science. Data visualization techniques help in representing complex findings in a visually intuitive manner, enabling stakeholders to grasp insights effortlessly. Deployment and Monitoring: The deployment of data-driven solutions and models marks the culmination of the data science process. Continuous monitoring ensures the performance and relevance of deployed models over time. Deciphering Data Analytics Data science and data analytics are two terms that frequently crop up in discussions surrounding data-driven decision-making. While they are often used interchangeably, they represent distinct methodologies and approaches to harnessing the power of data for organizational success. In contrast to the holistic approach of data science, data analytics primarily focuses on examining datasets to draw conclusions and make informed decisions. While data analytics shares some commonalities with data science, such as utilizing statistical techniques and visualization tools, its scope is often narrower, emphasizing descriptive and diagnostic analyses rather than predictive modeling or prescriptive recommendations.Data science encompasses various activities, including data collection, cleaning, exploration, modeling, and interpretation. It involves the application of advanced algorithms and machine learning techniques to extract meaningful insights from vast and complex datasets. Data scientists are skilled in programming languages like Python and R and in deploying tools such as TensorFlow and PyTorch for deep learning tasks. They possess a deep understanding of mathematical concepts, probability theory, and computer science principles, allowing them to develop sophisticated models for predicting future trends, optimizing processes, and identifying hidden patterns within data.On the other hand, data analytics tends to focus on utilizing historical data to understand past performance and inform present decisions. It involves data mining, clustering, regression analysis, and visualization to uncover trends, patterns, and correlations within the data. Data analysts often work with

Finding the best Data science courses in Mumbai is not difficult for anyone. We are here to assist you. We have compiled a list of the best data science institutes in Mumbai. To select the top data science institute, we considered a variety of aspects such as tuition fees, modules, placements, and so on. We are all living in the Digital era, which is set apart by its speed and pioneering possibilities. Everything that comes to mind has a global digital presence. Businesses, sellers, startups, MNCs, individuals, and purchasers are all going digital. Are you planning to go digital by learning data science? The exchange of information is the primary function of the internet. According to Naukri, there are presently 2952 job opportunities in Mumbai alone, which is significantly more than neighboring cities such as Navi Mumbai, Vashi, and Thane. According to Glassdoor, the average salary for a Data Science Engineer in Mumbai is 11,11,406 per year. Some of the best data science institutes in Mumbai are Rise Institute, ExcelR, MCTA, Techdata, etc. How can we get the word out to as many people as possible? Data Science is the answer. The knowledge of data science  empowers and equips you with the skills you need to transform data and make it beautiful, just like your imagination. Benefits of Data Science Course Benefits of Data Science Course Easy to learn Global Reach Business Analysis Enhance security Data science is versatile Decision making Better Customer Service Rise Institute has prepared a list of Top 10 Data science institutes in Mumbai. The question is, What you should look for while going through the list. The comparison will help you reach the final conclusion, which institute to join for Data science courses in Mumbai? The Basis of Comparison are- Course Modules Placements Experience of Faculties Mentor Support Data Science Education provides them a world of possibilities. The data science geography is both diversified and rich in detail. A hardworking student can build a full-fledged and successful profession. Some of the professional opportunities provided by data science include: Data Science Engineer Data Analyst Business Intelligence Analyst Statistician Data Architect Marketing Analyst List of Top 10 data science institutes in Mumbai Rise Institute Excelr Aegis.edu.in Simplilearn Mcta Digital vidya Collegedunia Scaler staragile Intellipaat To help readers differentiate the wheat from the chaff, we’ve created a list of the Top 10 Data Science Courses in Mumbai. 1. Rise Institute Rise Institute is the best learning platform for all data science courses in Mumbai. They present experts with over 15 years of market and market working conditions experience. The combination of curriculum, training, and the addition of live projects makes it the ideal technique to achieve successful student placement. Rise Institute offers a 100% data science course in Mumbai with placement. They have ties to influential organizations such as Facebook and Google. Rise Institute’s Data science courses in Mumbai have resulted in a number of success stories. Rise Institute began humbly in 2016, but since then it has never wasted a single breath and has always worked for excellence. Here are certain features of Rise Institute that set it different from the others. 100% Placement support Best training modules 30+ modules for data science Live projects EMI option available Mock interviews Resume making Innovative Futuristic Ideas Capstone Projects “Change is the law of nature,” according to the Rise Institute philosophy. In a growing industry, they have established practices that prioritize students, entrepreneurs, professionals, startups, freelancers, and anyone who want to develop a strong foundation through data science. Concept of Rise Institute Creativity Top-notch Training Optimal Learning Atmosphere Innovation Clear and Concise Problem Solving Continuous Improvement Contact Details Name – Rise Institute Address – Office no 36, Akshar Geometrix Silver Christ Kamothe, near Khandeshhwar, Sector-25, Khandeshhwar, Railway Station, Navi Mumbai, Maharashtra 410209 Phone no. – 7972131295 Website – riseinstitute.tech Email – riseacademy777@gmail.com Apply Now 2. FindMyTuition Are you also looking for the perfect ‘tuition hub in Noida’? If so then you don’t have to look any further! Learners can fulfill all their learning needs by taking personalized lessons with FMT. FMT offers study lessons through different learning modes, including:  Instant learning Home Classes Center Classes  Read on to the sections below to learn more about the FMT’s tuition hub in Noida, different learning sources, and more. Let’s proceed! FMT’s instant learning has marked the way to instant education and caters to all learning needs. It is designed to make learning easy by focusing on core concepts and skills in a particular time frame, enabling learners to obtain mastery quicker than traditional methods. This approach is for students looking to study remotely and upgrade their skills. With interactive lessons, real-time feedback, and personalized content, FMT ensures an engaging and effective learning experience. FMT also offers courses in Data Science, Data Analytics, and Generative AI course in UK, helping learners gain in-demand skills for a competitive job market. Embrace the power of instant learning with FMT and unleash your full potential, making learning more efficient and rewarding. Attributes of  FindMyTuition Expert Tutor 24/7 Assured Placement Support Emi Option Available Data Science Coure in UK Contact Details Name – Find My Tuition Email – info@findmytuition.com 3. Aegis school of Data Science Aegis School of Data Science is a well-known institution in Mumbai, India, that offers programs and courses in the field of data science. It is recognized for providing education and training in areas such as data science, big data, artificial intelligence, and related fields.Aegis provides 75% practical learning to help you refine your skills, grow your business, and find your first job. They are affiliated with  15+ institutions for placement and services. They have established levels for mentor programs. Since 2015, hundreds of Aegis data science graduates from over 40 batches (19 full-time and 22+ weekend) have successfully launched their careers as data scientists, AI engineers, Business Analysts, and others with a minimum package of 8.5 lacs to 40 lacs and up to 500% salary hike on the previous package with India’s best Post-Graduate