Why Join our PG Data Science and Engineering Course?
Looking forward to building a career in data science and analytics? The 5-month PGP-Data Science Engineering Course in Bangalore by Great Learning and Great Lakes is designed to equip students with valuable data science techniques and technologies, along with teaching them hands-on applications via industry case studies.
Pursuing this course can help candidates transition to the role like data analysts, business analysts, data engineers, and analytics engineers in the domain of data science and analytics.
Ranked #1 in analytics education
The PGP-Data Science Engineering Course in Bangalore by Great Learning and Great Lakes has been ranked rank #1 nationwide for four consecutive years now. It holds an average rating of 4.8 out of 5 based on parameters such as course structure, faculty, pedagogy, and brand value.
PG Certificate from Great Lakes
Upholding its repute as one of the leading business schools in India, Great Lakes is the youngest institute in the country to receive AMBA and UK accreditations.
World class faculty
The faculty at Great Lakes, with their years of experience and knowledge, is among the best you can find. Many of the faculty members at Great Lakes are among the nation’s top data science academicians.
Intensive bootcamp format
Following an intensive bootcamp format, the Data Science Course requires students to work in data science lab sessions for building their expertise, alongside being trained by a highly reputed faculty. The entire course duration is 20 weeks and includes 4 weeks of capstone projects.
Important tools and skills sought by leading Data Science companies have also been taken into consideration for preparing the course structure. By the end of this course, candidates are well-trained in SQL, Python, Data Science, Machine Learning and Tableau. To build their knowledge, candidates are given several challenging projects on different topics and applications in Data Science, in addition to classroom lectures.
The corporate network of Great Lakes is substantial and involves many leading names in the corporate sector that participate in its hiring drives. A few among such organizations are Mahindra, Cognizant, Flipkart, Big Basket, HSBC, and TVS to name a few.
The PGP-Data Science Course in Bangalore by Great Lakes is a comprehensive course that involves an amalgam of different learning methods like classroom lectures, industrial sessions with professional practitioners and practical exercises. Classes are held on weekdays and there are online discussions and assignments as well.
Classroom sessions are held at 9:30 a.m. from Monday to Thursday at the Great Learning centre.
There are regular lab sessions in class to assist candidates in applying their data science concepts to real-life scenarios, with thorough guidance from faculty members and industry experts.
4-Week project work
This involves an application-oriented industry project, directed and assessed by institute faculty and industry experts.
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 program offers Placement Readiness Evaluation at the end of the course, to help students prepare for interviews, on clearance of which students sit for the placements.
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 Axis Bank and Eduvanz 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 admissible for candidates in their final semester and fresh graduates with 0-3 years of experience. Candidates must possess an aggregate of 60% or above in Xth, XIIth, and Bachelors. Apply Now for Data Science Course Demo.
An industry-aligned and up-to-date course in Data Science
Many youngsters these days are passionate about learning data science and becoming a data scientist. Many working professionals are also dreaming to experience a transition in their careers by taking up a data science course. If you are somebody who belongs to any of the above two categories, you must know
- The reason why is that data science has attained a vast exposure and huge demand in no time?
- What is data science? How does it work? What is it's applications and benefits?
Data scientists play a vital role in any organization. From designing the plan to solving business problems, data science is involved in every aspect of the business.
Salary structure of Data Scientists in the country
Do you know that Data scientist job is one of the highest-paid job roles? Data scientist job roles are high in demand in the present day. Many industries are seeking several data scientists to fit in the On average, data scientists make around 620, 244 rupees per year. While the senior data scientists are expected to earn 1,147,826 rupees per year which is a huge amount.
Demand for Data Science in Bangalore
Bangalore, being the silicon valley as India, has got a huge demand for Data Science. Several industries are in queue to employ the techniques of data science. Many organizations are getting ready to embrace data science.
Bangalore currently has around 8346 openings for various job roles in the field of data science. The demand for data science is expected to encounter a rapid growth in the days to come. Considering this demand, many youngsters are enthusiastic about taking up a data science course in Bangalore to start an exciting career in the field of data science. This choice that you make definitely stands as the best as it lets you set your career on an outstanding platform that has got enormous demand in the market.
Data science is also expected to replace many existing job roles which is making many to run towards this amazing technology.
What are the prerequisites of taking up a data science course?
If you are dreaming to join the data science training program in Bangalore, it is necessary to understand the different prerequisites which you need to know before you take up the data science course.
TBeing good at mathematical concepts of linear algebra such as matrix, tensor operations, etc makes it easy to master Data Science. Other important mathematical traits you will need to be good at is Calculus. Data science involves a lot of calculus operations to optimize the data. Therefore, mathematics stands as a major prerequisite to understand the concepts of Data Science.
Possessing the knowledge of programming languages such as R, C, C++, Python, Hadoop, etc definitely smoothes your learning path. Being good at Excel makes mastering data science easy.
Python programming language is one of the major prerequisites of learning data science. Object-oriented python and python frameworks would be a great aid in understanding the concepts of data science.
Data science is more about statistics. Data science involves a lot of statistical tools to derive meaningful insights from the raw data. There are two types of statistics involved.
The descriptive analysis makes it easy for you to understand the data as it describes it. It involves concepts like Normal Distribution, Central Tendency, Variability, etc.
Inferential statistics help you derive solutions from the descriptions derived using descriptive statistics.
Data Visualization tools
One of the major job roles of a data scientist is to visualize the data. Possessing strong technical skills to display the data is very important. learning data visualization tools such as Tableau, Domo, Qlikview, etc would be a strong aid to learn data science.
What are the main job roles and responsibilities of a data scientist?
A data scientist is liable for analyzing the past data to predict and provide the most accurate plan for any organization. In other words, data scientists apply the analytical and technical skills to wisely extract sensible outputs from huge data sets. This process demands a lot of functions to be performed by a data scientist. Let us see what are the main roles.
- Data collection from different data sources.
- Data reporting.
- Cleansing raw data (both structured and unstructured) and segregating them accordingly.
- Building models using the past data to predict the future accurately.
- Develop business strategies.
- Identify the problems.
- Analyze and solve problems using data.
- Improve the accuracy of the data.
- Increase the overall operational efficiency.
- Cost reduction.
- Discover ways to provide a better customer experience.
- Remove hazards and minimize the risks.
What are the major tools and techniques employed by a data scientist?
Data scientists use various tools to perform several operations. Below is the list of the major toolset that any data scientist would employ.
- Analytical tools
- Data mining
- Statistical Analysis
- Data modeling
- Predictive models
- Data visualization tools
Applications of Data Science
Data science has been employed in various sectors for the amazing benefits that it offers. Data science has got a wider range of applications. Learning data science could benefit you get in a job role in any of the below mentioned sectors. Even as the list of the industries that apply data science is growing day by day, there is a vast area that welcomes you to be a data scientist.
Let us learn about the major applications of data science.
Data scientists do make this world a better place by solving the problems. Data science plays a key role in problem solving. Understanding the objectives and finding the accurate solution for the problems is definitely a challenging task which every data scientist would be facing on a daily basis.
The problem solving by data scientists involves three steps. They are defining a problem, structuring the data and the application of the programming languages. This technique of data science has been applied in several fields to solve major problems of their business.
Data science plays a vital role in the financial sector. Fraud detection and risk analysis are two of the many major applications of data science in the financial sector. Data science also helps in studying and understanding a customer's behaviors and promotes customer's risk modeling. These applications of data science cause great enhancement in the sector of finance.
E-commerce of another major sector which widely employs the techniques and tools of data science. Data science helps the e-commerce sites to promote outstanding customer experience by studying customer behavior and suggesting related products to the customer. Risk analytics is one of the major applications of data science in the field of E-commerce as it helps to understand and analyze the upcoming risks way before and help the organization to eradicate them.
Data science helps every industry to study and learn about its customers which will in turn have a great impact on gaining profits. The following are the few operations performed by data science in performing customer analytics
- Identifying the target customers.
- Customer data management.
- Promote great customer experience.
- Recommending related products based on previous purchases.
- Analyzing the reviews and ensuring.
- Constant enhancement in promoting a better experience for the customers.
Many manufacturing companies employ data science to enhance the quality of the products that they produce and regulate their services. Data science helps to provide constant monitoring of the machinery and Schedule maintenance.
Error detection is another major application of data science in the field of manufacturing as data science helps to detect the errors at a very early stage to rectify and eradicate them. This prevents the manufacturing sector from huge losses.
The healthcare sector robustly employs data science in performing various medical operations. Data science promotes efficient medical analysis. Data science is applied in image analysis to detect various diseases. Data science also aids in drug discovery and helps the doctors to prescribe the right medicine for the patients.
Data science has been strongly applied to the latest trends in transportation. One of the major examples we can quote to describe the application of data science in the field of automation and transportation is the introduction of self-driving cars.
Data science technology is also applied in the field of Gaming. From the development of the game to the design, functionality of the game, data science plays a vital role.
Data science also has got any applications in several fields. A few of the most regular applications of data science include image Recognition, Speech Recognition, Search Engine Optimization, Translation, etc.
Ensure that you get registered for taking up the best data science course in Bangalore and set up your career in the right path.