DATA ANALYST Learning path
Change the traditional approach to learning Data Analyst. Instead of spending months on maths and theory, focus on projects, practical skills and tech that in in-demand
We brought together some of the of best data analysts, AI and ML entrepreneurs, Kaggle grand masters to create Industry best courses and projects for you to build a 🤘 ROCKSTAR Data 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 Data Structures for solving complex problems.
✔ Learn about Lists, Tuples, Dictionaries, Sets, Stacks and Queues.
✔ Learn Sorting, and Searching Algorithms.
✔ Learn about Parameters and different Types of Arguments in a Function.
✔ Learn about Comprehensions and Anonymous Functions.
✔ Learn about OOPs Concepts.
✔ 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 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 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.
✔ Learn Univariate, Bivariate and Multivariate Analysis.
✔ Learn Animated and Interactive Data Visualizations.
✔ Plot Charts used in Finance, Marketing etc.
✔ 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.
✔ Learn advanced Data Transformations Techniques.
✔ Learn Encoding Techniques to deal with Categorical Data.
✔ Learn Cross Validation Techniques.
✔ Learn Techniques used for Treating Dimensionality.
✔ Implement Correlation Filtering, VIF, and Feature Selection.
✔ Implement PCA, LDA, and t-SNE for Dimensionality Reduction.
✔ Understand the Working of Linear Regression algorithm.
✔ Implement Linear Regression with RFECV and Cross Validation.
✔ Learn Evaluation Metrics used for Linear Regression.
✔ Understand the Working of Logistic Regression.
✔ Implement the Logistic Regression Algorithm with RFECV and Grid Search technique.
✔ Learn Evaluation Metrics used for Logistic Regression.
✔ 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 about SELECT, and WHERE Statements.
✔ Learn to use Logical Operators and aggregate Functions.
✔ Learn to use Order By and Group By Clauses.
✔ 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.
✔ Work on Big Datasets using Google Cloud Platform and Big query.
✔ Perform Data Visualizations on Big Data using Google Data Studio.
✔ Perform Big Data Analysis using Google’s Big Query Engine.
✔ Learn Basics of Data Visualizations using Tableau.
✔ Learn Advanced Tips and Techniques for creating Charts.
✔ Learn about Formatting Pane, Styling, Customizing tooltip and mark labels, etc.
✔ Learn to Handle and Manage the data using Tableau.
✔ Learn Joins, Blending, Sorting, Hierarchies, and Data Filters.
✔ Learn Mapping, Dashboarding and Story Boarding.
Top Projects that YOU will be doing
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.