Next Cohort Starts
Industry Practitioner Led Weekly Live Session
Individual Course Completion Certificate
Real Industry Projects
HBR Case Studies
1:1 Coaching & Mentoring
Monthly Skillathons
Career Labs
Hiring Talentathons
Go beyond Online Digital Learning to Experiential Learning. Learn the art of data visualization & storytelling. Understand various data science & business analytics techniques to drive your business growth through a data-driven approach, even without having a prior coding experience.
with 1:1 personalized executive coaching
bringing real-world board room context
to the classroom
Real-time skill building with best practices frameworks, problem solving assignments & 1:1 mentoring sessions.
with focus on "Experiential Learning"
real-time feedback from hiring leaders
Practice & implement new-age skills by working on real-time industry problems through comprehensive frameworks.
Industry recognised certification in Data Science and Business Analytics
Learn from top-tier global data science industry practitioners through live sessions, case studies and real-time projects using multiple industry-relevant tools. This is more than just a data science certification, it focuses on data-driven leadership, broadening your perspectives into strategy and decision-making roles, and helping you build a strong network of data and thought leaders.
Top Skills You Will Learn
Business Problem Framing, Insight mining, Business Inferencing using statistical techniques, Business Analytics, Exploratory Data Analytics and Feature Engineering, Prescriptive & Predictive Analytics, Data Analytics with Python, Data Visualization and Storytelling.
Who Is This Program for?
Domain Experts, Engineers, Marketing and Sales Professionals, Software and IT Professionals, Project Managers, Product Managers, Business Analysts, Consultants, Entrepreneurs, Finance Professionals
Minimum Eligibility
â– The applicant should have at least 5 year of work experience in a technical or business-related space and an undergraduate degree.
â– Â Prior knowledge of programming is not mandatory but preferred.
Job Opportunities
Data Analyst, Data Science Manager, Entry-level Data Scientist, Business Analyst, Data Product Manager, Marketing Analyst, Quality Analyst, Insight Manager.
Tools Covered
Data science is a multidisciplinary field of study. Hence, a good data science course prepares you for divergent niches. Explore the possibilities you can unlock with the best data science courses in India.
Why PGPDSBA? The Data Science and Business Analytics Course Advantage
If you are looking to build demonstrable skills, work on real-world challenges, make data-driven decisions, and build your brand by pursuing a Data Science certification, this may be the right program for you. We also understand that as a working professional, you may need strong hand-holding with dedicated support. Your learning experience manager will be there for you at every step to guide you in your learning journey.
Mastering demonstrable skills are not enough by itself for a successful career transition. You need to learn how the industry works, build a portfolio that gets you through the door, and effectively plan for your next career move. The data science course at IPL extends beyond the curriculum and supports you in all of these aspects.
Access to multiple
job openings
Personalized Resume & LinkedIn review
Guidance from Industry Practitioners
Career Planning & Mock
Interviews
Data Science and Business Analytics Course Curriculum
Data Science and Business Analytics Courses created and curated by industry CXOs with case studies, simulations, real-life projects, assignments and personalized coaching. The courses included in IPL’s data science certification program prepare you for diverse industry needs and focuses on building data-driven leadership qualities.
Course 1: BAN401F – Business Problem Framing
This course will help you to understand various problem-solving methods to find the most efficient solution to a business problem in a structured, understandable, and collaborative way.
Course 2: DSC401F – Data Analytics Foundations
The importance of statistics in data science and data analytics cannot be underestimated. This course provides tools and structured methods to get deeper data insights.
Course 3: DSC403F – SQL for Data Analytics
SQL for Data Analytics is very simple but powerful query-based language that will help you to handle databases and interact with data with ease.
Course 4: DSC404F – Python for Data Science
From applications in data science and software engineering to the AI and ML environments, learn python for data science and understand its strategic importance for decision-making.
Course 5: DSC405F – Data Science Foundations
Understand the fundamental statistical methods, lifecycles to learn data science concepts and solve real-time problems in a more efficient manner.
Course 6: DSC406F – Data Science Techniques
This course will help you understand how to extract knowledge from large amounts of data through Machine Learning to help you make better
data-driven decisions.
Course 7: BAN402F – Data Storytelling and Visualization
Every data point tells a story. Learn the art of storytelling and narrate an engaging data story. Learn how to visualize data using tools and communicate effectively through analysis and facts.
Typical Learning Path for each course
Data Science Framework of
European Union
Faculties & Mentors
Learn from India’s leading Data Practitioners.
Industry Projects and Case Studies
Learn through real-life projects and assignments across industries
In this competition, you’ll apply your machine learning skills to build a model that predicts which items are the same products. Your contributions to product matching could support more accurate product categorization and uncover marketplace spam. Customers will benefit from more accurate listings of the same or similar products as they shop. Perhaps most importantly, this will aid you and your fellow shoppers in your hunt for the very best deals.
In this challenge you will use a song’s attributes to predict a track’s ‘popularity’? The better the App can quantify music, the better they can tune their systems and algorithms to generate more revenue for themselves and their stakeholders.The goal is to see whether hit songs shared similar features, and if so, whether those features could be used to predict which songs would be hits in the future.
We may have some experience of travelling to and from the airport. We have used different cab services for this travel? Did you at any time face the problem of cancellation by the driver or non-availability of cars? The aim of analysis is to identify the root cause of the problem (i.e. cancellation and non-availability of cars) and recommend ways to improve the situation. As a result of your analysis, you should be able to present to the client the root cause(s) and possible hypotheses of the problem(s) and recommend ways to improve them.
Deciding whether a used car is worth the posted price when you see listings online can be difficult. Several factors, including mileage, make, model, year, etc. can influence the actual worth of a car. From the perspective of a seller, it is also a dilemma to price a used car appropriately. Determine whether the listed price of a used car is a challenging task, due to the many factors that drive a used vehicle’s price on the market. The focus of this project is developing machine learning models that can accurately predict the price of a used car based on its features, in order to make informed purchases.
Managing traffic problems in the metro cities. Modern cities are changing. The rise of vehicular traffic has been changing the design of our cities. It is very important to know how traffic moves in a city and how it changes during different times in a week. Hence it is very important to analyse and gain insights from traffic data. The challenge is to analyse the traffic data from Bengaluru. The data gives us some information about how traffic moves from source to destination under various circumstances.
Do you remember the days before Uber, Lyft, or Gett? Standing in the street trying to hail a taxi waiting for the moment a free cab might drive by and spot you? These days that world seems so far away. And you might often wonder: how do these apps work? After all, that set price is not a random guess. Given data from past rides, you are required to design the best taxi fare prediction machine learning model.
Predict the price of the listing. The company is an online marketplace for arranging or offering lodging, primarily homestays, or tourism experiences. Help the company’s data science team to predict prices of stay in the US based on attributes present in the dataset.
New users on this stay listing platform can book a place to stay in 34,000+ cities across 190+ countries. By accurately predicting where a new user will book their first travel experience, they can share more personalized content with their community, decrease the average time to first booking, and better forecast demand. In this challenge, you are given a list of users along with their demographics, web session records, and some summary statistics. You are asked to predict which country a new user's first booking destination will be. All the users in this dataset are from the USA.
In this challenge you need to determine the emotional background for a given letter (or a set of letters?). Testing will be performed on prepared sample letters, which will be provided to the teams directly during the final presentation. The results will depend on: 1) quality of the sentiment predicted by the model for given emails (during the presentation); metric - MAE (1 - Very negative, …, 5 - Very positive) 2) idea behind the proposed method 3) quality of the presentation.
Do you remember the days before Uber, Lyft, or Gett? Standing in the street trying to hail a taxi waiting for the moment a free cab might drive by and spot you? These days that world seems so far away. And you might often wonder: how do these apps work? After all, that set price is not a random guess. Given data from past rides, you are required to design the best taxi fare prediction machine learning model.
Cohort Profile
With a diverse cohort, learning becomes interesting and networking becomes impactful.
The data science course at IPL ensures that you maximize your learning opportunities through a diverse cohort with learners as Domain Experts, Engineers, Marketing and Sales Professionals, Software and IT Professionals, Project Managers, Product Managers, Business Analysts, Consultants, Entrepreneurs, Finance Professionals, Senior Decision Makers, and many other different walks of life.
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Frequently Asked Questions (FAQs)
Data analytics can be looked at as a subset of data science. Both the disciplines work in tandem to make sense of data. A data science professional builds models and finds out strategies to extract insights from data. An analyst is tasked with using analytical models to identify patterns in data. A data science certification program can help you take either way based on your specialization.
Big data defines the tools and the practices applied to collect, store, and manage large amounts of data as well as a large amount of data itself. Big data is useful because there is data science, and data science is applicable because of big data.
Mathematics is one of the key disciplines that make data science. As a data professional, you will be dealing with statistical models, and linear programming, hence mathematical knowledge is a pre-requisite. If you did not have maths during your academic years, or if you have lost the touch, there are training programs that can help you bridge the gap before you enroll in a data science course.
Mathematics is one of the key disciplines that make data science. As a data professional, you will be dealing with statistical models, and linear programming, hence mathematical knowledge is a pre-requisite. If you did not have maths during your academic years, or if you have lost the touch, there are training programs that can help you bridge the gap before you enroll in a data science course.
As a data science professional, you will be working with people as part of a team. It is very important to communicate effectively, build storytelling skills, and develop organizational habits. As a working professional, you must have developed these qualities over the years. During the data science course, you will have an opportunity to perfect these skills while working on projects.
There is no age limit when it comes to joining a data science certification course.
Data science combines mathematics, statistics, and computer science hence coming from a STEM background carries a heavy advantage. But if you are from a background like economics, or business, you can possibly take up a data science course. Yes, it will take extra effort on your part.
Predictive analytics is the study of data patterns to predict an outcome. It involves correlating multiple multiple data points to find insights. This can be used in a lot of different situations from disaster aversion to product pricing.
Yes, you can learn data science on your own with the help of free resources and even get deep into machine learning without undergoing a data science certification course. However, there are two issues – one, you need to spend a lot of time looking for resources that will be useful, and two, you will find it difficult to get your foot into a big company without a certification.
What is Data Science?
Data science is a multidisciplinary approach to extract meaningful insights from data by collecting, cleaning, studying, and analyzing it. It combines principles of mathematics, statistics, artificial intelligence, and computer engineering to locate patterns in data that lead to predictions and aid decision making.
Why should you pursue a data science course?
Data is the most important component in any business strategy. depending on data and its successful analysis, businesses can
With a masters in data science, you will learn to use data science effectively in a business context, and manage and manipulate its impact for the best results.
It has been more than a decade since data science left the academic closet and entered the real world. While in theory, it can bring outstanding positive impact to a business, its practical application and success are still quite unwarranted.Â
Analytical ventures fail just as often as they succeed. But this is a risk every business has to take lest they fall behind. The demand for data science skills has been rising consistently, and a data science certification gives you great leverage.Â
Why PG in Data science from IPL?
As a domain expert, sales manager, product manager, or business analyst, you already have solid business acumen. Your existing skills combined with IPL’s data science training turn you into an asset that businesses will find hard to lose and extremely difficult to refuse.
The data science certification program at the Institute of Product Leadership includes 7 courses that take 7 months to complete. These courses are designed for working professionals with 5+ years of experience. This data science course is ideal for you if you want to make the transition into a career in data-driven leadership. It also opens up a myriad of possible career paths that are happening, and industry relevant.
Every professional walk is getting augmented by artificial intelligence, and the disruption caused by it is touching every level from developers to product managers. A masters in data science course at this juncture can help you stay on the right side of disruption. Â
Career opportunities after completing a data science course
Data science is a multidisciplinary field that forks out into a number of different directions. Getting a data science certification or undergoing a data science online course does not necessarily translate into a career as a data scientist – it is one possibility among many. You can build a career as
Enrolling in our data science course with placement support and career assistance will help you find out the best way forward for yourself.
Applications of data science in various industries
The following are a few industries that put a lot of stress on data-driven process enhancement and business development. This is just to give you a glimpse of the diverse scope of the discipline and it is not nearly all-inclusive.
The Tech Giants - FAANG
The big five of the technology industry, Facebook, Amazon, Apple, Netflix, and Google, all spend extensively on data science and depend on data-driven insights to enhance customer experience, engagement, retention, and overall ROI. For instance, Netflix makes predictive data analytics to curate the movie and shows suggestions for your taste. How do you think Amazon comes up with the on-point additional product suggestions based on what you are buying? Similarly, Google does a stellar job at processing data to help you find what you are looking for faster.
The Healthcare Industry
The healthcare sector contributes 30% of the world’s data volume. It produces data at every level – from clinical trials to insurance data. There is still a lot of gaps in terms of data utilization when it comes to the healthcare sector. It is definitely an area that will have maximum traction for data-driven managers in the coming days.
Finance and Banking
The banking sector was among the first to employ data science extensively. It was primarily to identify potential loan defaulters. It is still among the industries that hires the highest number of data analysts.
The Oil and Gas Industry
The oil and gas industry makes a profit of $3 billion daily – a little breakdown here and an error there can cost millions of dollars. Data science is applied heavily by oil and gas companies to enhance processes, identify machinery that could malfunction in the future, and design efficient route maps, among other things.
Cyber Security
The hackers are getting better by the day. They have powerful scanners, large forums, and a lot of resources to draw from. Applied data science can go a long way in terms of predicting attacks, prescribing solutions, and recommending defensive measures.
Manufacturing and Retail
The issue of process enhancement comes back like a refrain. You cannot put enough stress on the importance of the small things – the location of a factory, the equipment you buy, the people you hire, the stores you invest in, everything can be optimized with the help of data.
Data is a key strategic element irrespective of the industries. It’s hard to identify any industry that does not apply data science. A PG in Data Science exposes you to potentially limitless opportunities.