Data Analyst
Duration: 6 Months

119,999.00

Category:

📜 Course Description

The primary goal of this course is to demystify Data Analytics and get the students acquainted with end-to-end Mastery of the complete process to access, manipulate, transform, analyze and visualize Data. This course is specifically designed as per the requirements and opportunities in the job market. The course covers complete Python and all the essential Python tools and Libraries for Data Analysis, Wrangling, Cleansing and Visualization . It’s more focused on teaching themainstream and in-demand tools with stable versions. Covers all the prerequisites & the foundation technologies.

🎯 Course Goals

Master skills with in-depth learning and get acquainted with the end-to-end tools to access, manipulate, transform, analyze and visualize Data.

Targeted Job Roles

  • Data Analyst
  • Data Mining Engineer
  • Data Research Analyst
  • Analytics Specialist
  • Data Engineer
  • Data Analytics Engineer

📝Curriculum

INTRODUCTION

  • Understanding Data Science
  • Understanding Data Analytics
  • Understanding Job roles
  • Data Ecosystem
  • Use Cases

PYTHON

  • Introduction to Python
  • Python variables, integers, indentation
  • Python Datatypes / Data structures
  • Statements
  • Operator / Loops / Functions
  • Exception Handling

PYTHON FOR DATA

  • Introduction to Numpy, SciPy,
  • Pandas, Matplotlib, Seaborn

DATA ANALYSIS (PYTHON)

  • Understanding Machine Learning
  • Understanding Data Science
  • Understanding AI
  • Timeline of Machine Learning
  • Use Cases

DATA WRANGLING (PYTHON)

  • Introduction to Python
  • Python variables, integers, indentation
  • Python Datatypes / Data structures
  • Statements
  • Operator / Loops / Functions
  • Exception Handling

DATA VIZUALIZATION (PYTHON)

  • Introduction to Python
  • Python variables, integers, indentation
  • Python Datatypes / Data structures

LINEAR ALGEBRA

  • Why Math ?
  • Mathematical Objects (Scalar, Vector, Matrix, Tensor)
  • Linear Algebra Notation
  • Linear Algebra Arithmetic / Stats
  • Matrix Operations / Factorization

STATISTICS

  • Statistical core concept
  • Descriptive Statistics
  • Inferential Statistics
  • Hypothesis Testing

PROBABLITY

  • Probability & Conditional Probability
  • Joint, Marginal, and Conditional Probability
  • Bayesian probability theory
  • Probability Distributions
  • Information
  • Probability Algorithms

DEMYSTIFYING DATA ANALYTICS

  • 360 degree view
  • the complete Process
  • Algorithms with Use Cases
  • Common terms and Concepts
  • DA vs DS

ESSENTIAL CONCEPTS L

  • Glossary
  • Modelling / Complete Process
  • Common Concepts
  • Common Properties and Assumption

COMPLETE SQL

  • SQL: Basics
  • SQL: Intermediate
  • SQL: Advance
  • Create, modify, and delete tables, views, and databases; load data; and store results of queries
  • Store and query complex or nested data structures
  • ETL

DATA PREPROCESSING

  • Need
  • Handling missing values
  • Handling features
  • Mean removal
  • Variance scaling

EXPLORATIRY DATA ANALYSIS

Introduction

Implementation on data