Data Science and Analytics with AI (Cohort-02)

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Course Content

Introductory Class

  • Data Science (Batch-02) – Introductory Class
    02:00:44

Class 01 –

Class 02 – Conditional Statements (IF, ELIF, ELSE) (Understanding IF Statement, ELSE Statement, ELIF Statement, Nested Conditional Statements, Practical Examples, Common Errors) | Loops and Control Flow (Introduction to Loops, FOR Loop, Iterating Over a Range, Iterating Over a String, WHILE Loop, Control Statements: BREAK, CONTINUE, PASS, Nested Loops, Practical Examples, Common Errors) | Setting Up Environment and Q&A Session

Class 03 – Python Lists: Introduction to Lists | Creating and Accessing List Elements | Modifying Elements | List Methods | Slicing Lists | Iterating Over Lists | List Comprehensions | Nested Lists | Practical Examples and Common Errors | Python Tuples: Introduction to Tuples | Creating and Accessing Tuples | Tuple Operations | Immutable Nature of Tuples | Tuple Methods | Packing and Unpacking Tuples | Nested Tuples | Practical Examples and Common Errors

Class 04 – Python Dictionaries: Introduction to Dictionaries | Creating and Accessing Dictionary Elements | Modifying Elements | Common Dictionary Methods | Iterating Over Dictionaries | Nested Dictionaries | Dictionary Comprehensions | Python Functions: Introduction to Functions | Defining and Calling Functions | Function Parameters | Default Parameters | Variable-Length Arguments | Using Return Statements

Class 05 – Functions and Functional Programming | Real-World Function Examples (Temperature Conversion | Shopping Cart Total | File Word Frequency | Email Validation – Assignment) | Lambda Functions – Syntax and Use Cases | map() Function for Element-wise Transformation | filter() Function for Conditional Selection | Introduction to NumPy | Importing Python Modules for Efficient Data Handling

Class 06 –

Power BI – Introduction of Power BI – Power Query

Power BI – Text Tools (Extract, Merge Columns, Split Columns, Format) | Number Tools (Statistics) | Reference Queries | Column Quality | Date Tools (Age, Time Series, Categorical)

Power BI – Conditional Column | Column for Example | Date Tools (Substract Days) | Group By | Filtering and Sorting | Parameters

Power BI – Append Queries | Select from Folder | Data Normalization Concept | Data Modelling

Power BI – Data Modelling | Star & Snow Flake Schema | Data Formatting | DAX Calculated Columns – Text Functions (LEFT, RIGHT, UPPER, LOWER, CONCATENATE, &) | Date Functions (DAY, MONTH, YEAR, DATEDIFF, TODAY)

Power BI – Text Function (SUBSTITUTE, FIND, SEARCH, Dynamic RIGHT, LEFT) | Date Functions (WEEKDAY, WEEKNUM) | Logical Operator | Logical Functions (IF, Nested IF)

Power BI – Logical Functions (Nested IF, SWITCH, SWITCH with TRUE, AND, OR)

Power BI – Measures | Implicit vs Explicit Measures | Filter Context | Filter Flow | Aggregation Functions (SUM, COUNT, COUNTROWS, AVERAGE, DISTINCTCOUNT, DIVIDE, MAX, MIN)

Power BI – CALCULATE | ALL | FILTER Functions | Variables and Commenting

Power BI – Iterator Functions (SUMX, AVERAGEX, MINX, MAXX) | Time Intelligence Functions (DATEADD, PREVIOUSMONTH, PREVIOUSYEAR, PREVIOUSQUARTER, SAMEPERIODLASTYEAR, DATESYTD, DATESMTD, DATESQTD, DATESINPERIOD)

Power BI – Handling Errors | Data Visualization (Navigation Bar, Images, Card Visual, Visual Formatting)

Power BI – Data Visualization (Line Chart, Forecasting, Reference Line, Bar Chart, KPI Charts, Donut Chart, Pie Chart)

Power BI – Data Visualization (Visual, Page, Report Level Filters, Basic Filter, Advanced Filters, TOPN Filter | Table Visual | Matrix Visual | TOPN Cards Visual | Slicer | Area Chart)

Power BI – Data Visualization (Guage Chart) | Drilling (Up, Down, Through) | Bookmarks | Page Navigation | Custom Tooltips | Conditional Formatting

Power BI – Project 01 – Oodles of Noodles

Power BI – Project 01 – Oodles of Noodles

Power BI – Project 02 – Market Mindz

SQL – SQL – Introduction to Database | Clauses (SELECT, FROM, WHERE, GROUP BY Statements) | TOP N | TOP N PERCENT Keyword

SQL – SQL – Clauses (HAVING, ORDER BY) | SQL Order of Operations | Aggregation Functions (SUM, COUNT, AVG, MAX, MIN) | Numerical Functions (ROUND, CEILING, FLOOR) | Date Functions (DATENAME, MONTH, DATEDIFF, DATEADD) | String Functions (CONCAT, UPPER, LOWER, CHARINDEX, LEFT, RIGHT, LEN)

SQL – SQL – Comparison Operators | IS and IS NOT Function | Conditional Functions (AND, OR, IIF, CASE – WHEN, THEN) | ISNULL Function

SQL – SQL – JOINS (INNER, FULL/OUTER, LEFT, RIGHT) | ER Diagram | Facts vs Dimension Tables | Relationships in SQL | UNION for Appending Queries

SQL – SQL – LIKE Function | CREATE VIEWS | Sub Queries (Scalar Query, Multi Row Query)

SQL – Sub Queries (Derived Column in SELECT, Derived Table in FROM) | Windows Functions (OVER(), PARTITION BY, ROW NUMBER, RANK, DENSE RANK. LAG & LEAD)

SQL – Data Cleaning in MySQL

Class 07 –