Data Analyst

Discover our Data Analyst Course, designed to equip you with the skills to manipulate data, conduct statistical analyses, and create insightful visualizations using tools like SQL and Python.

business_people_working_for_data_analytics_graph_report_dashboard_and_monitoring_for_business_marketing_planning_and_finance_investment_concept

ENROLL NOW

Total Courses

Level

Beginner

Duration

25 Days

Schedule

Flexible

Earn a professional certificate

Update your LinkedIn profile, resume, or CV with this certification. Share it on social media and during your performance evaluations.

Certificate icon. License paper. Best quality warranty

Key Features Of This Course

Comprehensive Program: Covers fundamental concepts including data manipulation, statistical analysis, and data visualization.

Hands-on Experience: Utilizes industry-standard tools like SQL, Python/R, and business intelligence platforms for practical learning.

Real-World Applications: Involves practical projects and case studies to apply skills in analyzing complex datasets.

Actionable Insights: Focuses on deriving actionable insights and making informed business decisions through rigorous analysis.

Skill Proficiency: Prepares you to handle diverse data scenarios and excel as a proficient Data Analyst in today’s dynamic data-driven environment.

SKILLS COVERED

Data Analysis

SQL Database Management

Excel Proficiency

Business Intelligence Tools

Networking

Industry-Relevant Skills

Critical Thinking

Hands-on Projects

Course Details

Data Analysis Introduction

1. Data analysis
3. Difference between Data analyst & Data Scientist
4. Roles & Responsibilities of Data Analyst
5. Different types of Data

Exploratory Data Analysis

1. What is exploratory data analysis?
2. 7 steps in EDA?
3. How to perform EDA on Real time Dataset

Data Visualizations

1. Getting Started With Tableau
2. Data and Connections
3. Creating Charts
4. Adding Calculations to Your Workbook
5. Mapping Data
6. Visualizations

Matplotlib

1. Bar plots
2. Matplotlib concepts
3. Subplots
4. Histograms

Advanced Data Analysis

1. Data Visualization
2. Correlation and Regression
3. Data Ethics and Privacy

Data Analytics for Business

1. SQL Fundamentals
2. Excel Data Analysis
3. Segmentation and Clustering
4. Data Wrangling

Data Analytics and Machine Learning

1. Statistical Software
2. Python
3. Jupyter
4. Collection and Preparation
5. Data Processing
6. Segmentation and Clustering

Data Analytics for Big Data

1. Data Storytelling
2. Data Wrangling
3. Exploratory Data Analysis (EDA)
4. Data Exploration and Cleaning

young beautiful woman in casual clothes holding laptop happy and positive looking at camera smiling confident showing thumb up standing over blue background

GET 100% JOB PLACEMENT BY ENROLLING IN CERTIFIED TRAINING COURSE

Enter Your Details Now

JOB ROLES

Data Analyst

Business Analyst

Business Intelligence Analyst

Database Administrator

Frequently Asked Questions

What do you mean by Data Analysis?

Data analysis refers to the process of inspecting, transforming, and modeling data with the goal of discovering useful information, supporting decision-making, and extracting insights.

What is Data Cleaning?

Data cleaning, also known as data cleansing, is the process of identifying and correcting errors, inconsistencies, and missing values in a dataset to improve its quality and accuracy for analysis.

What is Feature Engineering?

Feature engineering is the process of selecting, extracting, or creating new features from raw data that are most relevant to the predictive modeling task at hand. It involves transforming data into a format that a machine learning algorithm can understand better, improving model performance and accuracy.