Data Science and Engineering

Great Lakes Institute of Management

in partnership with Great Learning

Great Lakes Institute of Management

in partnership with Great Learning

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Full disclaimer.

Who should attend

Participants from the course have secured roles such as Data Scientists, Machine Learning Engineers, Data Analysts, Analytics Consultants, etc.

Eligibility

  • Applicants should have 60% or above in Xth, XIIth and Bachelor's degree.
  • The program is open for candidates in their final semester and recent graduates with 0-3 years of experience.
  • The PG Data Science Course is ideal for candidates with a graduation in a quantitative discipline like engineering, mathematics, commerce, sciences, statistics, economics, etc.

About the course

Data Science Course | Data Science Certification | Data Science Training - Great Learning

Why Join our PG Data Science and Engineering Course?

Great Lakes PG Data Science and Engineering Course is a 5-month classroom program for fresh graduates and early career professionals looking to build their career in data science & analytics. Candidates from the course are able to transition to roles such as business analysts, data analysts, data engineer, analytics engineer etc. by learning relevant data science techniques, tools and technologies and hands-on application through industry case studies.

Ranked #1 in analytics education

Great Lakes’ program has been ranked #1 in India for 4 years in a row, and has an average rating of 4.8/5 across parameters like Course Content, Pedagogy, Faculty, and Brand Value.

PG Certificate from Great Lakes

Great Lakes is one of India’s top 10 business schools, the youngest institute in India to receive an AMBA, UK accreditation, and a leader in analytics education.

World class faculty

You gain from the decades of experience and expertise brought to the table by Great Lakes faculty in their chosen domains. Several of Great Lakes faculty have been ranked among India’s top Data Science academicians.

Intensive bootcamp format

The data science course follows an intensive bootcamp format where you learn data science and machine learning from expert faculty in classroom and deepen your expertise by working on data science lab sessions. The course duration is 20 weeks including 4 weeks of capstone project.

Hands-on learning

The course covers the tools and skills sought by leading companies in Data Science. Through the duration of the course, candidates are trained on Python, SQL, Tableau, Data Science and Machine Learning. Participants in the course build their knowledge through classroom lectures by expert faculty and doing multiple challenging projects across various topics and applications in Data Science.

Placement assistance

Through the corporate network of Great Lakes, several leading companies participate in the hiring drives organised for PG Data Science Course candidates. Some of the companies that have recently participated in the hiring process of PG Data Science and Engineering Course include: Uber, Swiggy, Fractal Analytics, Oyo, KPMG, Mu Sigma, Mercedes Benz, Cognizant, Mahindra, Big Basket.

Program Structure

The 5-month PG Data Science Course uses a combination of learning methods that include classroom teaching, hands-on exercises, and sessions with industry practitioners. Classes are conducted on weekdays and are assisted by online discussions and assignments.

Classroom learning

Classroom sessions by our top-ranked faculty would be conducted from Monday to Thursday starting 9:30 AM at the Great Learning center.

Lab sessions

Regular in-class lab sessions help candidates apply data science concepts to real-life scenarios under the guidance of a faculty and industry expert.

4-Week project work

Candidates work on an application-oriented industry project where they are mentored and evaluated by Great Lakes 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.

Curriculum

Our corporate partners are deeply involved in curriculum design ensuring that it meets the current industry requirements for data science professionals.

Foundations

Introduction to programming using Python

  • Syntax and Semantics of Python programming
  • Conditional statements
  • Loops
  • Iterators
  • User-defined functions
  • NumPy
  • Pandas

Exploratory Data Analysis

  • Pandas
  • Summary statistics (mean, median, mode, variance, standard deviation)
  • Seaborne
  • matplotlib

Statistical Methods for Decision Making

  • Probability distribution
  • Normal distribution
  • Poisson's distribution
  • Bayes’ theorem
  • Central limit theorem
  • Hypothesis testing
  • One Sample T-Test
  • Anova and Chi-Square

SQL Programming

  • Introduction to DBMS
  • ER diagram
  • Schema design
  • Key constraints and basics of normalization
  • Joins
  • Subqueries involving joins and aggregations
  • Sorting
  • Independent subqueries
  • Correlated subqueries
  • Analytic functions
  • Set operations
  • Grouping and filtering

Machine Learning Techniques

Linear and Logistic Regression

  • 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

Supervised Learning Classification

  • CART
  • KNN (classifier, distance metrics, KNN regression)
  • Decision Trees (hyper parameter, depth, number of leaves)
  • Naive Bayes

Unsupervised Learning

  • 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

Ensemble Techniques

  • Bagging & Boosting
  • Random Forest
  • AdaBoost & Gradient boosting
  • Hackathon

Applications

Time Series (Online Instruction)

  • Trend and seasonality
  • Decomposition
  • Smoothing (moving average)
  • SES, Holt & Holt-Winter Model
  • AR, Lag Series, ACF, PACF
  • ADF, Random walk and Auto Arima

Text Mining (Online Instruction)

  • 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

Data Visualization (Online Instruction)

  • Building interactive dashboards using Tableau
  • Data Visualization using Tableau

(2) New Messages!

Data Science Course | Data Science Certification | Data Science Training - Great Learning

Experts

Abhinanda Sarkar

Dr. Abhinanda Sarkar is the Academic Director at Great Learning for Data Science and Machine Learning Programs. Dr. Sarkar received his B.Stat. and M.Stat. degrees from the Indian Statistical Institute (ISI) and a Ph.D. in Statistics from Stanford University. He has taught applied mathematics at ...

Mukesh Rao

Prof. Mukesh Rao is an Adjunct Faculty at Great Lakes for Big Data and Machine Learning. Mukesh has over 20 years of industry experience in Market Research, Project Management, and Data Science. Mukesh has conducted over 100 corporate trainings. Data Science training covers all the stages of CRI...

Gurumoorthy Pattabiraman

Gurumoorthy is a Techno-Functional Professional with over 10 years of experience in the IT & Analytics domains. He is an undergrad in Mathematics & postgrad in Actuarial Economics. He has headed the Global Analytics Team in one of the World's largest Shipping Companies and currently is th...

D Narayana

Dr. Narayana holds a PHD in Mathematics from Pierre and Marie Curie University, Paris, France. Dr. Narayana has more than 11 years of industry experience and over 4 years academic research experience. Over these years, he has worked as a professor, trader, project manager, team lead, and develop...

Srabashi Basu

Srabashi is an analytics expert and an academic administrator. She does extensive work in statistical applications in different areas like health analytics, complex data analytics, aviation industry, CRM etc. She has published research papers in many areas of statistics and is always eager to app...

Mudit Kulshreshtha

Dr. Kulshreshtha’s career has spanned over 15 years both in industry and academics. Dr. Kulshreshtha’s significant industry experience encompasses CXO level and leadership positions across 3 industry domains – Retail, Financial Services & Energy; with organizations like PAYBACK (American Expr...

Rajesh Jakhotia

Rajesh is a Business Intelligence and Analytics Professional with over 15 years of experience, he is the Founding member of K2 Analytics Finishing School Pvt. Ltd. His past work experience includes working with Fractal Analytics, Sutherland Global Services and Hansa Customer Equity and Positive ...

R Vivekanand

Vivek Anand is a data visualization consultant with 10 years of experience. His area of specialization includes Marketing and Econometrics. Vivek has an MBA from Monash University Melbourne Vic. He has worked as Sales & Marketing professional handling teams of leading Indian hospitality brand...

Videos and materials

Data Science and Engineering at Great Lakes Institute of Management

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Full disclaimer.

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