MASTERING
Business Analytics
WHO IS THIS PROGRAM FOR
IS THIS PROGRAM YOUR PERFECT MATCH?
Aspiring Data Analysts:
If you have a passion for data analysis and want to build a career in the field of business analytics, this program is tailor-made for you. Gain the necessary skills to excel in data-driven decision making and unlock a world of opportunities.
Working Professionals:
Already in a business or analytical role but aiming to specialize in business analytics? This program is designed to enhance your analytical skills and empower you to drive data-centric strategies within your organization.
Mid-Career Advancers:
Midway in your career and eager to transition into the high-demand domain of business analytics? This program will equip you with the expertise needed to thrive in data-driven industries and propel your career forward.
DISCOVER THE WORLD OF
BUSINESS ANALYTICS:
Immerse yourself in the dynamic realm of business analytics, where data insights and statistical techniques drive critical business decisions. Explore the power of data visu-alization, predictive modeling, and machine learning to solve complex business chal-lenges.
WHY CONSIDER A CAREER IN BUSINESS ANALYTICS?
Growing Demand: In today’s data-centric world, businesses seek skilled analysts to interpret and leverage data for competitive advantage.
Lucrative Salaries: Business analysts are in high demand, commanding attrac-tive remuneration and growth opportunities.
Decision-Making Power: By interpreting data, you can contribute to strategic decisions that shape business outcomes.
Versatility: Business analytics skills are applicable across industries, opening doors to diverse career options.
TOP SKILLS YOU'LL MASTER
Data Analysis and Visualization:
Acquire proficiency in data wrangling, exploration, and
visualization using tools like Tableau and Power BI.
Predictive Analytics:
Learn how to build predictive models and use statistical techniques
to forecast future trends and outcomes.
Machine Learning:
Understand the fundamentals of machine
learning and apply algorithms to solve real-world business problems.
R Programming:
Gain expertise in R programming language, widely
used for data analysis and statistical computing.
UNLEASH YOUR POTENTIAL IN BUSINESS ANALYTICS WITH EDUVERSE'S DIVERSE TOPICS:
- Introduction to Business Analytics.
- Data Exploration and Visualization Techniques.
- Predictive Modeling and Regression Analysis.
- Machine Learning Algorithms and Applications.
- Big Data Analytics and Hadoop Framework.
- Text Analytics and Sentiment Analysis.
- Customer Analytics and Market Segmentation.
- Supply Chain Analytics and Inventory Optimization.
- Business Intelligence and Dashboard Design.
PROGRAM DETAILS
Program Duration & Format
6-month online program.
Program Start Date
For information on the next start date, please refer to our website.
Eligibility
Time Commitment
Tuition Fee
The total program fee is 60,000, inclusive of all taxes. This investment in
your future includes all the course materials and access to our renowned
faculty.
THE MODULES
Python programming language
Installing Python on your computer; Jupiter notebooks. Using pip or similar command for installing various packages such as Pandas Matplotlib or Numpy. Reading data from csv files into Panda data frame. Using Matplotlib to plot one or more series of data. Descriptive statistics. Linear regression and Logistic regression.
Statistical methods - I
Probability, Games of Chance, Conditional, Marginal and Joint Probability, Bayes’ Law, Sampling methods and empirical rules, sample mean and central limit theorem, standard normal distribution and probability table. Student’s t-distribution.
Statistical methods - II
Framing mutually exclusive hypothesis, setting a significance level for type I error and typeII error. Testing for means – single sample, testing for proportions – single sample. Testingfor difference of means – two large
samples, testing for difference of proportions – two large samples, small
samples and t- test statistic. hypothesis tests for paired samples, Chi-square test for independence of population attributes. Chi-square test for goodness of fit of distribution, correlation coefficient for categorical data
Statistical methods - III
scatterplots and regression line, ordinary least squares regression, estimating the coefficients, testing for their significance, coefficient of determination, F statistic and fitness of overall model. Applications of regression, multiple regression, estimating betas for multiple regression. Odds, log of odds. Sigmoid function, Classification with logistic regression; Issues using regression for binary classification.
R programming languages
Installing R and/or RStudio on your computer. Installing packages. Reading csv files into R. Calculating summary measures. Counts and pivot tables in R. Sampling from various distributions. Hypothesis tests. Linear regression and logistic regression
Statistical methods - IV
Experimental design, completely randomised design, randomised block
design, factorial experiment, one way ANOVA for more than two populations, Pearson’s correlation coefficient, Spearman’s rank correlation.
Data Analysis for Business Management
Market Basket Analysis and Associative Rule Mining, Text analysis, Decision Trees, Data Visualisation, Cluster Analysis
Business Forecasting Techniques - I
Qualitative methods and quantitative methods. Method of Delphi, Jury of
Executive Opinion etc. Calculating a moving average. Exponential
smoothing. Exponential smoothing with trend and seasonality
components.
Business Forecasting Techniques. -II
Time Series Analysis, seasonality, stationarity, decomposition a series into
trend, seasonality, cycles and random variation. Box-Jenkins methodology.
Dealing with non-stationarity, Tests for stationarity.