Advance Full Stack Data Analyst Program by Cleancode - Fees, Syllabus, Certifications, Placements | Online and Offline Training Available - Expert Trainers - Micro Batches - Global Certifications

Master fundamental data analysis concepts, statistical methods and tools, deepen proficiency in Python languages, Data Wrangling and Cleaning, Data Visualization, Exploratory Data Analysis (EDA),Machine Learning Fundamentals, statistical analysis, Database Management, API Integration, Web Scraping, Cloud Computing for Data Analysis, Model Deployment.

JOB ASSISTANCE PROGRAM!

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1000+

Students Trained

180+

Hours of Lectures

Google Ratings:

4.8

Duration

4 to 6 Months

Hybrid Mode

Online + Offline

Micro Batches

15 Students Only Batch Size

Eligibility

Anyone

Beginner Friendly

Beginner to Advance Training

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Recognized and Certified By

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Course Offerings

Job Assistance

Daily Assignments and Exercises

Interview Preparations

Doubt Clearing

Resume Building

Mock Interviews

Study Material and Resources

Micro Batches

Regional Trainers

Beginner Friendly Curriculum

Internship Letter

Global Certifications

Course Curriculum

Introduction to Excel Formulas:

Introduction to Excel Formulas Overview of Excel as a Spreadsheet Tool Importance of Formulas in Excel Basic Formulas in Excel SUM Function AVERAGE Function MEAN Function MEDIAN Function SUMPRODUCT Function CONCATENATE Function Advanced Formulas in Excel VLOOKUP Function INDEX Function MATCH Function IF Function COUNTIF Function SUMIF Function Data Management Techniques Removing Duplicates Conditional Formatting Using Charts for Data Visualization Data Manipulation and Analysis Filters in Excel Sorting Data Slicers for Enhanced Data Exploration Pivot Tables and Pivot Charts Introduction to Pivot Tables Creating Pivot Tables Analyzing Data with Pivot Tables Creating Pivot Charts.

Applications in Data Analysis and Decision Making :

Introduction to Math and Statistics Importance of Mathematics and Statistics Applications in Data Analysis and Decision Making Basic Math Operations Arithmetic Operations Weighted Average Calculation Cumulative Sum Calculation Percentile Calculation Basic Statistics Measures Mean (Arithmetic Mean) Median Mode Standard Deviation Normal Distribution .

SQL :

Introduction to SQL Overview of SQL (Structured Query Language) Importance in Database Management Basic SQL Queries SELECT Statement WHERE Clause DISTINCT Keyword LIKE Operator BETWEEN Operator ORDER BY Clause LIMIT Clause Grouping and Aggregation GROUP BY Clause HAVING Clause Aggregate Functions (SUM, AVG, COUNT, MAX, MIN) Data Modification INSERT Statement UPDATE Statement ALTER Statement Importing Data into SQL Data Types in SQL Overview of Common Data Types Numeric, Character, Date/Time, Boolean Advanced SQL Queries Date and Time Functions Window Functions Subqueries Case Statements Common Table Expressions (CTE) Introduction to CTEs Utilizing CTEs in Queries Query Optimization Strategies for Query Optimization Indexing and Performance Improvement Joins in SQL INNER JOIN OUTER JOIN (LEFT, RIGHT, FULL) Understanding Join Relationships

BI Tools (Power BI) :

Introduction to Power BI, Power BI Dashboard, Connectors, Table Transformations, Data-Modelling, DAX-Functions, Dashboard Creation, Artificial Intelligence (AI) Visuals

Python Programimg :

Introduction to Python Programming Overview of Python Importance in the Programming Landscape Python Basics Variables and Assignments Data Types in Python Operators in Python Data Structures in Python Lists Tuples Dictionaries Sets Conditional Statements and Loops Conditional Expressions if Statements Loops (for, while) Functions and Modules Defining Functions Modular Programming with Modules Classes and Objects in Python Introduction to Object-Oriented Programming (OOP) Creating Classes and Objects Python Libraries: Pandas and Matplotlib Introduction to Pandas and Matplotlib Importance in Data Science and Visualization Pandas for Data Manipulation and Analysis Reading and Writing CSV, Excel, and JSON Files Working with DataFrames Data Manipulation: Group By, Concatenate, Merge Matplotlib for Data Visualization Creating Static Visualizations Animated Visualizations Interactive Visualizations in Python

Get Certified

Advance Full Stack Data Analyst

Once you have completed the course, assignments, exercise and submit the projects you will be able to generate the certificate and be eligible for placements

Attendance of at least 80% of the classes.
Completion of 80% of the projects and assignments assigned by the Company.

Note: Internship letter and global certifications will be issued exclusively upon the successful completion and submission of 80% of the projects and assignments.