Change the traditional approach to learning Business Analyst. Instead of spending months on maths and theory, focus on projects, practical skills and tech that in in-demand
World-class faculty from top academic centres and corporates across Europe and USA.
We brought together some of the of best data scientists, AI and ML entrepreneurs, Kaggle grand masters to create Industry best courses and projects for you to build a 🤘 ROCKSTAR Business Analyst in you.
✔ Learn Basic formatting, and different Data Types in Excel.
✔ Learn Analytical and Aggregate Functions in Excel.
✔ Learn Text, Logical, and Statistical Functions in Excel.
✔ Learn about Data Cleaning and Preparation Functions.
✔ Learn to make Pivot Tables and Pivot Charts in Excel.
✔ Learn Data Visualizations and Dashboarding in Excel.
✔ Learn to create a Databases, and Tables with proper validations and Constraints.
✔ Learn different types of Joins in SQL.
✔ Learn to Handle Complex Queries using Sub Queries in SQL.
✔ You will learn to create simple dashboards.
✔ You will learn about the dimensions, measures and filtering data.
✔ You will learn to prepare the Charts, and Maps.
✔ You will learn about the Formatting Pane, Styling, Customizing tooltip and mark labels, etc.
✔ You will learn about managing data, Data extraction, Joins and blending, etc.
✔ You will learn about sorting, groups, hierarchies, sets, data filters.
✔ You will learn about maps, layers, geocoded fields, WMS, etc.
✔ You will learn about storytelling, dashboards, Containers, dashboard actions.
✔ Learn about Variables, Data Types, and Operators in Python.
✔ Manipulate Python strings using In-built functions.
✔ Understand the Concept of Loops and Conditionals.
✔ Learn Data Structures for solving complex problems.
✔ Learn about Lists, Tuples, Dictionaries, Sets, Stacks and Queues.
✔ Learn Sorting, and Searching Algorithms.
✔ Learn about Date and Times and Regular Expressions.
✔ Learn Numpy for Complex Mathematical Operations.
✔ Learn Pandas in depth for Data Frame Manipulation.
✔ Learn Bayes Theorem, Basic and Conditional Probabilities.
✔ Learn Normal Distributions, Skewness, and QQ Plots.
✔ Learn Central Limit theorem, and Confidence Intervals.
✔ Learn the Types of Error in Hypothesis Testing.
✔ Learn to implement t-Test, z-Test and their types.
✔ Learn ANOVA, Chi squared Goodness Tests, and Chi square Test of Independence.
✔ Learn to analyze the Target Data using the Dabl library.
✔ Learn Pandas Profiling for analyzing the whole data at once.
✔ Learn about the Sweet Viz for Comparing Datasets.
✔ Learn to Handle Missing values in a Real-world Scenario.
✔ Learn to Handle Outliers in a Real-world Scenario.
✔ Learn Data Manipulation Functions for Cleaning the Data.
✔ Perform Grouping Operations and Filtering Operations.
✔ Perform Interactive Query Analysis using Ipy Widgets.
✔ Learn Cross Tabulation using Cross Tabs.
✔ Learn to Extract Features from Dates and Times.
✔ Learn to Extract Features from Numerical Data and Categorical Data.
✔ Learn Advanced Functions to Extract New Features from the Data.
✔ Implement Machine Learning Algorithms.
✔ Learn Regularization Techniques such as Ridge, Lasso, and Elastic Net.
✔ Learn Feature Selection, Hyper Parameter Tuning for Improving the Model.
✔ Implement Decision Trees and Random Forestsusing Sklearn.
✔ Learn Gini Index and Information Gain.
✔ Understand the working of Random Forests and Decision Trees in Depth.
✔ Understand the Concept of Boosting using Ada Boosting Gradient Boosting.
✔ Learn to implement the XG Boost Model.
✔ Learn about the Ensembling Techniques used to Enhance Accuracy of Predictive Models.
✔ Understand the Concept of Over Sampling and Under Sampling.
✔ Implement Over Sampling and Under Sampling Techniques.
✔ Using XG Boost for Imbalanced Data sets.
✔ Understand the Working of K Means, Hierarchical, and DBSCAN Clustering.
✔ Implement K Means, Hierarchical, and DBSCAN Clustering using Sklearn.
✔ Learn Evaluation Metrics for Clustering Analysis.
✔ Learn Techniques used for Treating Dimensionality.
✔ Implement Correlation Filtering, VIF, and Feature Selection.
✔ Implement PCA, LDA, and t-SNE for Dimensionality Reduction.
✔ Learn to Process and Prepare a Time Series Data.
✔ Learn Advanced AR Models ARIMA, ARIMAX, SARIMA, and SARIMAX.
✔ Learn Evaluation Metrics for Time Series Models.
Instructor Led Program
Self Paced Program
Meet some of our Extremely Talented and Hardworking Alumnis at DataisGood Career Transition Programs who achieved their Dream Jobs as a Data Scientist and Data Analyst in some of the Most Reputed MNCs and Startups.