Example Curriculum
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Introduction Dists Analytics, Types of Analytics, How Data Analyst and Business Analyst Different Scope of Data Analytics and Business Analytics
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Calculation Functions Basic and Advance and Formulas V lookup , H lookup , and Lookup
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Logical functions , text functions , Conditional formating( Basic and Advance )
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Pivot tables in details , Table , slicers , timers, Data analysis in Excel.
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Chars, power query, Stats Introduction
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What is Statistics, Types of Statistics, Descriptive Statistics, Inferential Statistics, Central Tendency, Measure of Central Tendency and Spread
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Types of Errors in Machine Learning Population and Sample Test in Inferential Statistics, P-value Tables and Critical value, Confidence Interval , T-test Significance, alpha Critical value, Degree of freedom.
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Types of Errors in Machine Learning Population and Sample Test in Inferential Statistics P-value Tables and Critical value Confidence Interval T-test
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T-test in detail Chi-square in detail Anova in detail , Chi-square in detail with practical implementation . Anova in detail with practical implementation.
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Introduction to Python , Intro to IDE, how to install anaconda, Julyter etc
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Introduction of python, Statements, Indentations, Comments, Variables , Datatype, Typecasting, Type Conversion, Input and Ouput Statements
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Operators, control flows, built-in data structures.
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Working with Text and All Important Methods of Text. Regular Expressions.
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Working with Text and All Important Methods of Text. Regular Expressions.
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Regular Expression, Function, Arguments, Parameters.
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Function Lambda Function, File handling Exception Handling.
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File handling Pandas Introduction Pandas Import Export
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Data Inspection, Data Cleaning, Data Manipulation
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Numpy Matplotlib,Data Aggregation, Custome Aggregation Join , merge, Concatenate DataFrames
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Seaborn •Standardization and Normalization •Multicollinearity •Encoding •Box Plot and IQR
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EDA Step By Step How to Install SQL
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What is Database ? •Types of Databases •What is Structured Query Language (SQL) ? •Database Structure •Creating our First DataBase •Simple Query •SQL Datatypes •Categories of SQL Commands •Database related Queries •Table Related Query •Primary Key and Foreign Key •Constraints in SQL
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Clauses in SQL Table Related Queries Joins in SQL Foreign Key In details
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Union and Union All Subqueries in Detail Window Function in Detail 1 NF :Normalization
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Normalization in detail Dimensional Modelling Facts and Dimensions Start Schema and SnowFlex Schema Views in My sql
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Architecture PBI, PBI Intro, Power Query Charts, Q and A Section, Filters and Slicers Drill Through Tooltip
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Top and Bottom Charts ,Building a Live Dashboard using all Functionality, Simple Dax
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Calculated Columns detailed Drill Down Drill Through Measures Basic
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Introduction to Power BI DAX Why DAX is Important in Power BI Scope of Usage with DAX. Usability Options DAX Context: Row Context and Filter Context DAX Entities: Calculated Columns and Measures Fundamental Functions in DAX Parameter in Power BI
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New Parameter (Numeric Range and Field) M Language What is M-Mesh Language Security : Manage Roles and View As Connect Data to Mysql Database Schedule Refresh in Power BI Basics of Machine Learning Supervised Ml vs Unsupervised ML
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Linear Regression Mathematical Intuition in Detail. Lasso Regression Ridge Regression Practical Implementation of Linear Regression (Python Code)
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Multiple Linear Regression Mathematical Intuition in Detail. Logistic Regression Mathematical Intuition in Detail. Practical Implementation of Multiple Linear Regression(Python Code) Practical Implementation of Logistic Regression(Python Code) Evaluation Metrics Regression and Classification
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Logistic Regression Mathematical Intuition,KNN Regression Mathematical Intuition,KNN Classification Mathematical Intuition,Practical Implementation of KNN Regression(Python Code),Practical Implementation of KNN Classification (Python Code),Evaluation Metrics Classification,Confusion Matrix in Detail
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Normalization Standardization Unsupervised Algorithms K-means Clustering Mathematical Intuition In Detail Hierarchical Clustering Mathematical Intuition In Detail K-means Clustering Code Explanation in Detail Hierarchical Clustering Code Explanation in Detail
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Assignment
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Decision Tree Classification Mathematical Intuition In Detail,Decision Tree Regression Mathematical Intuition In Detail,Decision Tree Classification Python Code Decision Tree Regression Python Code
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PCA- Dimensionality Reduction Python Code In Detail, Deep Learning Introduction, Artificial Neural Network, Single Neural Network, Back Propagation, Weight Updation Formula
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Weight updation Formula Vanishing Gradient Problem Activation Functions Loss Function (MSE,MAE,Huber Loss, Loss Function, Categorical Cross Entropy) Softmax Activation Function Linear Activation Function Optimizers (Gradient Descent, SGD,Minibatch SGD)
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Optimizers ( SGD with Momentum, Adgrad) Project: 1.Customer Segmentation 2.Customer Lifetime Value 3. Churn Prediction
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NLP Introduction Text Preprocessing Tokenization Stop words Stemming Lemmatization One hot encoding Bag of words TF-IDF Word to Vector Practical Implementation of NLP Task
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Adam Optimizer ANN Implementation NLP- Sentiment Analysis ML Project(Next Purchase Day)
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Career Building Session
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14th June
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15th June
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16th June
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17th june
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18th June
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Career Building Session
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Further Placement Assistance Process
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