TOP RANKED DATA ANALYSIS COURSE

Advanced data analysts are equipped to tackle complex data problems, make informed decisions, and drive insights that can lead to innovation, optimization, and growth in various domains, including business, science, healthcare, and technology.

ADVANCED PYTHON

TABLEAUE

POWERBI

DATA ANALYSIS TOOL OF PYTHON

STATISTICAL ANALYSIS

EXPOLITORY DATA ANALYSIS

Module 1: Introduction to Data Analysis

1.1. What is Data Analysis? 1.2. Types of Data 1.3. Data Analysis Process 1.4. Tools and Software for Data Analysis 1.5. Ethical Considerations in Data Analysis

Module 2: Data Collection and Preparation

2.1. Data Sources and Collection Methods 2.2. Data Cleaning and Preprocessing 2.3. Dealing with Missing Data 2.4. Data Transformation and Standardization

Module 3: Exploratory Data Analysis (EDA)

3.1. Descriptive Statistics 3.2. Data Visualization 3.3. Exploring Data Distributions 3.4. Identifying Outliers and Anomalies

Module 4: Statistical Analysis

4.1. Hypothesis Testing 4.2. Confidence Intervals 4.3. Correlation and Regression Analysis 4.4. Analysis of Variance (ANOVA) 4.5. Non-parametric Tests

Module 5: Data Visualization

5.1. Graphs and Charts 5.2. Creating Effective Visualizations 5.3. Dashboard Design 5.4. Interactive Data Visualizations

Module 6: Predictive Analytics

6.1. Introduction to Predictive Analytics 6.2. Linear and Logistic Regression 6.3. Decision Trees and Random Forest 6.4. Clustering and Classification 6.5. Model Evaluation and Selection

Module 7: Time Series Analysis

7.1. Time Series Data and Components 7.2. Decomposition and Forecasting 7.3. Autoregressive Integrated Moving Average (ARIMA) 7.4. Exponential Smoothing Methods

Module 8: Data Mining and Pattern Recognition

8.1. Clustering Analysis 8.2. Association Rule Mining 8.3. Outlier Detection 8.4. Text Analysis and Natural Language Processing (NLP)

Module 09: Experimental Design and A/B Testing

09.1. Experimental Design Principles 9.2. Conducting A/B Tests 9.3. Analyzing A/B Test Results 9.4. Optimization and Decision-Making

Module 10: Data Ethics and Privacy

10.1. Ethical Considerations in Data Analysis 10.2. Data Privacy and Security 10.3. Regulatory Compliance (e.g., GDPR)

Module 11: Capstone Project

11.1. Applying Data Analysis to Real-World Problems 11.2. Project Proposal and Design 11.3. Data Collection and Analysis 11.4. Presentation and Report

Module 12: Career Development

12.1. Career Paths in Data Analysis 12.2. Resume Building 12.3. Job Search Strategies 12.4. Interview Preparation

Duration: 2-3Months

Projects: 8+ Nos

Assignments Every Modules

1:1 Mentorship till Advanced Python

Course Fee: FEE: 26500/-
Fees (EMI Mode) : 26500/-
Fees (One time Payment mode) : 23500/-

What You Will gain After This Course:

1. Master Advanced Techniques: Learn complex data analysis methods and machine learning algorithms that set you apart.

2. Hands-On Tool Experience: Gain practical skills with industry-standard tools like Python, Data Analysis/Data Visualization Advanced Tools, Tableau/PowerBi

3. Real-World Problem Solving: Develop the ability to tackle real business challenges using data-driven insights.

4. Build Your Portfolio: Create a portfolio of projects that showcases your skills to potential employers.

5. Boost Your Career Opportunities: Open doors to high-demand roles in various industries with competitive salaries.