Example Curriculum
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Induction Session - 15 September
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Python, Applications of Python, Variable, Data Types - Operators , Control statement (if & else)
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Completed all control flow statements, Range Function, Started with string and it's methods
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Completed String theory as well methods, Done with List Data Structure, Done with Tuple's theory and methods, Hands on practice for these three data structures on jupyter notebook
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Completed Set theory as well methods, Done with Dictionary Structure, Hands on practice for all data structures, Started with Built-In-Functions
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Started with Lambda Functions - User defined Functions - Global and Local Variable with global and local functions - Hands on practice for each topics on Jupyter notebook - Function Arguments
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Modules in Python - Math and Random Modules - Exception Handling - Hands on practice for each of them - Files in Python - File Operations - Data Science Introduction
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Business Intelligence Theory - Data Mining Theory - Analytics Theory - Excel Functions - Basic formula - Date Formula - Logic Formula - All if and ifs functions
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Lookup functions: Vlookup, Hlookup, Xlookup - Excel Shortcuts - Pivot table - How to create Pivot? - Creating reports using pivot tables.
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Data Analysis using Pivot Table - Pivot Charts - Report Building and filters in Pivot - Advance Excel - Data Analysis (Correlation, Regression, Co-variance, Moving Average, Descriptive stats) - Goal Seek
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Scenario Manager - Power Query Introduction - Loading, Transformations - Data Visualization - Reporting - Story Telling - Dashboard
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New section
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INTRODUCTION TO POWER BI - CREATING POWER BI REPORTS, AUTO FILTERS - REPORT VISUALIZATIONS AND PROPERTIES
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New section
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Numpy Theory - Numpy Functions - Flatten, Ravel, etc. - Have practiced all Numpy functions in Jupyter Notebook - Assignment can be found in same Notebook file
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Pandas Theory - Series and it's functions - Series manipulation - Data Frame - Data Frame manipulation and different functions - Practiced Jupyter notebook code for it
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Accessing rows and columns in dataframe - Updating values in dataframe - Sorting DataFrames - Groupby in Pandas - Deleting value in dataframe - Read and write a file using pandas - Started with concept of Joins in Pandas
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Joins and its code in python - Data Preprocessing - Data Wrangling - No Assignment today just practice whatever code we have done
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Handling Categorical and Numerical Features - Outlier Detection and Imputation - Exploratory Data Analysis (EDA) - Sampling (Train-Test Split)
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Standard Scaling, Normalization - Introduction to Matplotlib - Matplotlib Installation - Line Plot in Matplotlib - Scatter Plot in Matplotlib - Pie chart in Matplotlib - Handling Outlier for multiple cols(updated code)
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Bar Graph - Histogram - Polar plot - Seaborn demonstration - Creating Subplots - Loading Iris Dataset - Scatter plot on Iris Features
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3D Scatter Plot - Pair Plots - Histogram and PDF - Univariate Analysis - Variance, Standard Deviation, Median - Heatmap, Violin - Boxplot, Donut Chart - SQL Installation
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Introduction to Databases - Why SQL? - Load Data - Use, Describe, Show Table - Select - DDL and DML concepts - Primary, Foreign and Unique Key
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TRUNCATE, DELETE - Operators - Aggregating Functions - Group By - Joins - Subqueries
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Window Functions - Views - Stored Procedures - Data Wrangling
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Data Analysis in SQL - Overview of Data, Overview of Statistics, Descriptive Statistics, Functions in Descriptive Statistics, Hands on in Python
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Inferential Statistics - Probability Distributions - Hands on Python - Introduction to Machine Learning
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Linear Regression - Model Building for - Simple Linear Regression - Multiple Linear Regression - Polynomial Linear Regression
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Classification Analysis - Logistic Regression - KNN - Diagnostics of Classifications - ROC and AUC curve - Code for Logistic and KNN
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Decision Tree theory - Decision Tree classification and regression code - Introduction to Random Forest
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Random Forest Theory, Project using Random Forest Algorithm, K-means Clustering theory and intuition , Code on K-means, Introduction to Hierarchical Clustering
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Completed Hierarchical Clustering , Code on Hierarchical Clustering, Introduction to Deep Learning , Epochs, Activation Function, Neural Network, etc. ,Code for Implementation of Deep Learning
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Time Series Forecasting - Introduction to NLP - Tokenization - Stemmizer - Lemmatization - Stop Words
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POS Tags - Sentence Segmentation - Feature Extraction from Text - Text Classification - Sentiment Analysis
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New section
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Append, Group & Merge in Power BI - Dates & Hierarchies, Drill Down - Line Chart - Editing Relationships between charts
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