Applied Data Analytics

Overview

Begin your journey with the Applied Data Analytics Specialization, designed for both beginners and professionals. This program equips you with essential skills in Python, SQL, and Power BI to analyze, visualize, and extract actionable insights.

Explore key concepts like data visualization, SQL queries, predictive modeling, and building dashboards. Through hands-on projects and case studies, gain the expertise to build predictive models, create dynamic dashboards, and solve business challenges effectively.

The specialization comprises four comprehensive courses:

Applied Data Analytics with Python and SQL:

Master data manipulation, querying, and analysis using Python and SQL. Python for Data Visualization and Analysis:

Learn to create impactful visuals and perform exploratory data analysis using Python libraries like Matplotlib, Seaborn, and Plotly.

Predictive Modeling with Python:

Develop and optimize machine learning models for actionable insights. Advanced Analytics with Power BI:

Leverage Power BI to create interactive dashboards and reports to derive actionable insights for making data-driven decisions.

By the end of this program, you’ll be ready to solve complex data challenges, deliver impactful insights, and advance your career in analytics. Join us to unlock the full potential of data and make meaningful contributions in any industry!

Syllabus

• **Course 1: Applied Data Analytics with Python and SQL**
• Introduction to Data Analytics
• Introduction to Python for Data Analysis
Python Environment Setup
Data Structures: Lists, Dictionaries, DataFrames
Data Manipulation with Pandas
• SQL for Data Analytics
Introduction to SQL Syntax
Writing Basic to Advanced SQL Queries
Joining and Transforming Data with SQL
• Practical Application and Case Study
• **Course 2: Python for Data Visualization and Analysis**
• Fundamentals of Data Visualization
Importance and Principles of Effective Visualizations
Choosing the Right Type of Chart
• Data Visualization with Matplotlib
Creating Basic Plots
Customizing and Styling Plots
• Advanced Visualizations with Seaborn and Plotly
Creating Complex Statistical Charts with Seaborn
Interactive Visualizations with Plotly
• Exploratory Data Analysis
Techniques for Data Summarization
Identifying Trends and Patterns
Practical EDA Project
• **Course 3: Predictive Modeling with Python**
• Introduction to Machine Learning
Types of Machine Learning: Supervised vs Unsupervised
Data Preprocessing and Feature Engineering
• Building Predictive Models
Linear and Logistic Regression
Decision Trees and Random Forests
Model Evaluation and Performance Metrics
• Advanced Topics in Predictive Modeling
Hyperparameter Tuning and Model Optimization
Introduction to Neural Networks
• Predictive Modeling Project
• **Course 4: Advanced Analytics with Power BI**
• Introduction to Power BI
Power BI Interface and Workflows
Connecting to Data Sources
• Data Transformation and Modeling
Cleaning and Shaping Data
Creating Relationships between Datasets
• Building Interactive Dashboards
Designing and Customizing Reports
Implementing Advanced Visualizations
• Advanced Features in Power BI
DAX Expressions and Calculated Measures
Power BI Service and Sharing Dashboards
• Capstone Project: Developing a Complete Analytics Solution
• **Program Completion and Career Advancement**
• Integrating Skills for Comprehensive Analytics Solutions
• Case Studies and Real-World Applications
• Career Pathways in Data Analytics

Taught by

Edureka

Subjects

Data Science