Data Science

Data Science

Data Science and Big Data Analytics are exciting new areas that combine scientific inquiry, statistical knowledge, substantive expertise, and computer programming. One of the main challenges for businesses and policy makers when using big data is to find people with the appropriate skills. Good data science requires experts that combine substantive knowledge with data analytical skills, which makes it a prime area for social scientists with an interest in quantitative methods.
This course integrates prior training in quantitative methods (statistics) and coding with substantive expertise and introduces the fundamental concepts and techniques of Data Science and Big Data Analytics.
Typical students will be advanced undergraduate and postgraduate students from any field requiring the fundamentals of data science or working with typically large datasets and databases. Practitioners from industry, government, or research organisations with some basic training in quantitative analysis or computer programming are also welcome. Because this course surveys diverse techniques and methods, it makes an ideal foundation for more advanced or more specific training. Our applications are drawn from social, political, economic, legal, and business and marketing fields.

Freshers from BCA, BCS, BE, BTech, MTech, MCA. MCS
Final Year/Internship projects for BCA, BCS, BE, BTech, MTech, MCA. MCS
Non IT Professionals who’ve worked mostly with tools like Excel and want to learn how to use R for statistical analysis.
Business Analyst
IT Project Managers
MBA Graduates or business professionals who are looking to move to a heavily quantitative role.
Engineering Graduate/Professionals who want to understand basic statistics and lay a foundation for a career in Data Science
MBA Graduates or business professionals who are looking to move to a heavily quantitative role.
Engineering Graduate/Professionals who want to understand basic statistics and lay a foundation for a career in Data Science

Forecasting Stock and Commodity Prices
Analysing Wine Types and Quality
Build your own image recognition model with TensorFlow
Customer Segmentation and Effective Cross Selling
Predict fraud with data visualization & predictive modelling
Analysing Movie Reviews Sentiment
Analysing Music Trends and Recommendations
Spam Detection
Build your own Recommendation System
Build your own Python predictive modelling, regression analysis & machine learning Model
Football Players (Estimating Population Mean from a Sample)
Election Polling (Estimating Population Proportion from a Sample)
A Medical Study (Hypothesis Test for the Population Mean)Employee Behavior (Hypothesis Test for the Population Proportion)
A/B Testing (Comparing the means of two populations
Customer Analysis (Comparing the proportions of 2 populations)
Predictive medicine: prognosis and diagnostic accuracy
Virtual assistance for patients and customer support
Creation of drugs – allows choosing, which experiments should be done and incorporates all the new information in a continuous learning loop
Clustering algorithms for customer segmentation
Discovering similarities across my Spotify music using data, clustering and visualization
An End-to-End Project on Time Series Analysis and Forecasting with Python
Using LSTMs to forecast time-series
Evolution of a salesman: A complete genetic algorithm tutorial for Python
A Machine Learning Approach — Building a Hotel Recommendation Engine
How To Create Data Products That Are Magical Using Sequence-to-Sequence Models

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