Why Join our PG Data Science and Engineering Course?
Ranked #1 in analytics education
The PGP Data Science Engineering Course by Great Lakes has been ranked as #1 in the country for 4 years in a row, with parameters like Pedagogy, Faculty, Course Content and Brand Value receiving an average rating of 4.8/5.
PG Certificate from Great Lakes
Counted among the top 10 B-Schools in India, and a leader in analytics education, Great Lakes is the youngest institute in the country to receive an AMBA, UK accreditation.
World class faculty
Several of the faculty members at Great Lakes has been ranked among the top Data Science academicians in the country. Here, you can gain from the decades of expertise and experience that the faculty brings to the table.
Intensive bootcamp format
The duration of this program is 20 weeks, which also includes 4 weeks of capstone projects. It follows an intensive boot-camp format. Here, you get to learn about data science and machine learning, which is taught by an expert faculty in a classroom format. You are further given the chance to deepen your expertise with data science lab sessions.
Throughout the program, candidates are trained on the tools and skills in Data Science which leading companies seek. This includes training in SQL, Tableau, Python, Machine Learning, and Data Science. With classroom lectures by expert faculty and multiple challenging projects on various topics and applications, this Data Science program helps the participants build their knowledge of the field.
Great Lakes has a great corporate network. This ensures the participation of several leading companies in the hiring drives that are organized for the candidates of the PGP-Data Science course in Chennai. Some of these companies include HSBC, Marlabs, Kantar, Jana Finance, TVS, Vestas, Flipkart, Big Basket, Mahindra, Cognizant Technology Solutions, etc.
The PGP-Data Science Engineering Course, in its duration of 5 months, involves combining different learning methods like classroom teaching, hands-on application, and holding sessions with practitioners of the industry. The classes, assisted by online discussions and assignments, are held on weekdays.
The classroom sessions are provided by an expert faculty, Mondays through Thursdays, and are held at the Great Learning center, starting at 9.30 AM.
Candidates get the guidance of a faculty and an industry expert to apply data science concepts they have learned to real-life scenarios in regular in-class lab sessions.
4-Week project work
The Data Science Course Candidates are mentored and evaluated by industry experts and Great Lakes faculty as they work on an application-oriented industry project.
Great Lakes Certificate & ePortfolio
Earn a Great Lakes certificate and create an ePortfolio to showcase your learning & projects in a snapshot. Your certificate and ePortfolio can also be shared on social media channels to establish your credibility in Data Science.
Our corporate partners are deeply involved in curriculum design ensuring that it meets the current industry requirements for data science professionals.
- Syntax and Semantics of Python programming
- Conditional statements
- User-defined functions
- Summary statistics (mean, median, mode, variance, standard deviation)
- Probability distribution
- Normal distribution
- Poisson's distribution
- Bayes’ theorem
- Central limit theorem
- Hypothesis testing
- One Sample T-Test
- Anova and Chi-Square
- Introduction to DBMS
- ER diagram
- Schema design
- Key constraints and basics of normalization
- Subqueries involving joins and aggregations
- Independent subqueries
- Correlated subqueries
- Analytic functions
- Set operations
- Grouping and filtering
Machine Learning Techniques
- Multiple linear regression
- Fitted regression lines
- AIC, BIC, Model Fitting, Training and Test Data
- Introduction to Logistic regression, interpretation, odds ratio
- Misclassification, Probability, AUC, R-Square
- KNN (classifier, distance metrics, KNN regression)
- Decision Trees (hyper parameter, depth, number of leaves)
- Naive Bayes
- Clustering - K-Means & Hierarchical
- Distance methods - Euclidean, Manhattan, Cosine, Mahalanobis
- Features of a Cluster - Labels, Centroids, Inertia
- Eigen vectors and Eigen values
- Principal component analysis
- Bagging & Boosting
- Random Forest
- AdaBoost & Gradient boosting
- Trend and seasonality
- Smoothing (moving average)
- SES, Holt & Holt-Winter Model
- AR, Lag Series, ACF, PACF
- ADF, Random walk and Auto Arima
- Text cleaning, regular expressions, Stemming, Lemmatization
- Word cloud, Principal Component Analysis, Bigrams & Trigrams
- Web scrapping, Text summarization, Lex Rank algorithm
- Latent Dirichlet Allocation (LDA) Technique
- Word2vec Architecture (Skip Grams vs CBOW)
- Text classification, Document vectors, Text classification using Doc2vec
- Building interactive dashboards using Tableau
- Data Visualization using Tableau
Learn from the Best
Learn from leading academicians and experienced industry practitioners in the field of data science.
Participants from the course have secured roles such as Data Scientists, Machine Learning Engineers, Data Analysts, Analytics Consultants, etc. Here are some of the companies that have recently participated in the PG Data Science Course hiring drives:
The PG Data Science Course has been designed to help candidates jumpstart their careers in Data Science. Here is what some of our PG Data Science Course candidates have to shared.
Balaji V R
Jana Small Finance
Jana Small Finance
- done Applicants should have 60% or above in Xth, XIIth and Bachelor's degree.
- done The program is open for candidates in their final semester and recent graduates with 0-3 years of experience.
- done The PG Data Science Course is ideal for candidates with a graduation in a quantitative discipline like engineering, mathematics, commerce, sciences, statistics, economics, etc.
Fill application form
Admissions committee will review and shortlist.
Screening call with Alumni/ Program Director/ Faculty
Shortlisted candidates are required to appear for an online aptitude test.
Candidates can pay the program fee through
Our tie-ups with several lending partners like HDFC Credila, Avanse (DHFL), MoneyTap, Credifiable, and Axis Bank ensure that money is not a constraint in the path of learning.
Upcoming Application Deadline
We follow a rolling admission process and admissions are closed once the requisite number of participants enroll for the upcoming batch. So, we encourage you to apply early and secure your seat.Apply Now
Frequently Asked Questions
The PG Data Science course is appropriate for those candidates pursuing their final semester and recent graduates with 0-3 years of experience. All the applicants must possess 60% or above in Xth, XIIth, and Bachelor's. Apply Now for Data Science Course Demo.
An industry-aligned and up-to-date course in Data Science in Chennai
If you are one of the many enthusiastic youngsters who is desiring to start their career in data science? Or are you one of the many working professionals seeking the right opportunity to take up a data science course for encountering a career breakthrough? Learn more about data science if you are extremely passionate about starting a new career in this booming field.
Before we learn much exciting stuff about the current day's buzz word, data science, let us know what it is exactly.
What is data science?
Data science is a vast subject that comprises multiple disciplines employing several structures, patterns, systems, algorithms and many more to derive the needed and meaningful insights from a particular set of data whether it is structured or unstructured. A person who works on data science is usually called as a data scientist.
The following are the major steps performed by any data scientists on a daily basis
- Data acquisition
- Data preparation
- Data analysis
- Data modeling
- Data visualization
- Data deployment
- Data maintenance
What are the different job roles offered to someone that pursues a data science course?
Apart from data scientists, let us see what are the several job roles that can be offered in this specific field. Since data science has enormous demand and is being adopted by many industries, there are many job roles and many responsibilities being assigned to the people working in this field.
- Data reporting executive
- Business Analyst
- Data engineer
- Data architect
What are the different roles and responsibilities of a data scientist?
Understanding the business problem
Before a data scientist could perform any operation, the first and foremost responsibility is to clearly understand the business problem. Understanding the problem also includes determining the objectives.
Asking several questions to avoid confusion and get the right information is also one of the major job roles of a data scientist.
Once the problem is understood, a data scientist gathers data from multiple channels such as web servers, databases, etc. Retrieving the right data isn't an easy task as it demands a lot of effort and time.
This process is divided into two categories. Namely, data cleaning and data transformation, The process of data cleaning consumes a lot of time as a data scientist encounters multiple complex scenarios to deal with. Working on inconsistent databases, duplicate data, misspelled attributes, etc are examples of the complex issues. Data transformation is the process of modifying the cleaned data considering the determined mapping route. Transforming the data that is understandable by the people involved in the project is a challenging task which any data scientist would encounter on a daily routine.
Data analysis is the process of understanding what to be done with the derived data by applying various tools of data science. This process involves defining and refining of the data. Data analysis is the most important phase of data science as it involves discovering the right way to execute the process using the given data.
Data modeling is applying various approaches and systems to get the best model that fits the requirements to solve the existing business problems. Training the data models and testing them are two continuous processes involved in this specific phase of data science.
Data visualization and communication
Creating effective reports is an important job role of a data scientist. Communicating with the clients and other people involved in the data science project to describe the derived solution by using various data visualization tools.
Before deploying the project, data scientists will have to test them in a preproduction environment. Once it is successful, the data scientists would deploy it to the clients.
Once the project is delivered maintaining the analytics of the performance of the project would be the last duty involved in a data science project.
Scope for Data science in Chennai
Statistics state that there exits around 4000+ large scale and 8000+ small and medium scale industrial companies within the city of Chennai. Chennai is one of the most popular cities in our country that promotes IT services.
Hence there exists an enormous scope for the field of Data Science in Chennai. Currently, there are around 600+ job openings for different job roles in the field of data science. Hence making data science as a career is a wise choice. If you are a resident of Chennai or you desire to move there for finding a career opportunity, ensure that you take up the most prestigious and high in demand data science course in Chennai and give a kick start to your career.
What are the major prerequisites of learning a data science course?
Knowing different programming languages such as R, Python, C++ etc is a major prerequisite of learning a data science course. Being good at excel is an add on for learning data science. Python programming language is highly preferred in data science especially in the phase of data modeling.
Statistics is a major aspect of data science as data science work more on the application of statistical theories. In fact, one who pursues a data science course can also be referred to as a statistician. So, it is very important to be good at statistical concepts such as variability, normal distribution, etc help understand the various important modules of data science.
Data Visualization tools
The application of data visualization tools is one of the daily routines of any data scientist. So, it is necessary to have knowledge of the data visualization tools such as Tableau, click view, Power BI to make it easy for the clients as well as the other people working through this project.
What are the various sectors that apply data science?
Health care Industry
Data science gives the best understanding of the genetic issues and helps to understand the patient's reaction for any specific drug. This empowers a doctor to prescribe the best medicine for his patients.
Data science is also employed in the field of education. It serves various purposes such as monitoring the student needs, introducing the innovative curriculum, etc and enhance the learning methodologies of the education sector.
Logistics companies are employing the techniques of data science to discover the best route to deliver a particular product. This saves a lot of time, money and effort on a daily basis contributing to the profit of these companies. Data science also helps the logistics sector to promote better customer experience.
Human Resource Management
Data science is being applied in human resource management to understand and analyze an employee's performance. This helps any organization to recognize and reward their employees.
Airlines are now employing data science techniques to predict the accurate landing time, delay time etc which makes the passengers comfortable and better their traveling experience.
In the past decade, data science has become a need for many sectors and industries to serve various purposes. Apart from the above-mentioned industries, there are many more sectors employing data science in their businesses. There is an unbelievable scope for the profession above-mentioned in the field of Data science especially in cities like Chennai. Start an amazing career by choosing to take up an amazing Data Science course in Chennai.