Advance Certificate In Full Stack Data Analytics

Advance Certificate In Full Stack Data Analytics course is offered by IIT FMS Computer Institute. We are passionate about empowering minds through cutting-edge education. Our mission is to cultivate creativity and expertise, shaping a bright digital future for our students.

With experienced instructors, hands-on training, and a commitment to excellence, we invite you to join us on this exciting journey of learning and growth. Discover your potential with us!

Course Content:

• **Module 1: Introduction to Data Analysis**
• - What is Data Analysis and its Importance
• - Types of Data Analysis: Descriptive, Predictive, Prescriptive
• - Data Analysis Process: Steps and Framework
• - Role of Data Analysts in Decision-Making
• **Module 2: Data Collection and Preparing**
• - Data Collection Methods and Sources
• - Data Cleaning and Quality Assurance
• - Data Transformation and Feature Engineering
• - Handling Missing Data and Outliers
• **Module 3: Excel for Data Analytics**
• - Excel Fundamentals for Data Analysis
• - Data Cleaning and Formatting in Excel
• - Data Visualization with Excel Charts and Graphs
• - Using Excel for Basic Statistical Analysis
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• **Module 4: SQL Fundamentals**
• - Introduction to Databases and SQL
• - Querying Data with SELECT, WHERE, GROUP BY, JOIN
• - Aggregation Functions and Subqueries
• - Working with Multiple Tables and Complex Queries
• **Module 5: Python Programming for Data Analysis**
• - Introduction to Python and its Data Analytics Libraries
• - Data Manipulation and Analysis with Pandas
• - Data Visualization with Matplotlib and Seaborn
• - Basic Statistical Analysis with Python
• **Module 6: Power BI Essentials**
• - Introduction to Power BI and its Capabilities
• - Data Importing and Transformation in Power BI
• - Creating Interactive Visualizations: Charts, Graphs, Maps
• - Building Dashboards and Reports for Data Insights
• **Module 7: Data Visualization and Storytelling**
• - Principles of Effective Data Visualization
• - Advanced Visualization Techniques: Heatmaps, Treemaps, etc.
• - Using Data Visualizations to Convey Insights and Tell a Story
• - Designing Engaging and Informative Data Dashboards
• **Module 8: Predictive Modeling and Machine Learning**
• - Introduction to Predictive Modeling
• - Regression Analysis: Linear, Multiple, Polynomial
• - Classification Algorithms: Decision Trees, Random Forests, etc.
• - Model Evaluation and Selection
• **Module 9: Text Analytics and Natural Language Processing (NLP)**
• - Processing Text Data: Tokenization, Lemmatization
• - Sentiment Analysis and Text Classification
• - Introduction to NLP Libraries: NLTK, spaCy
• - Extracting Insights from Textual Data
• **Module 10: Real-world Data Analytics Projects**
• - Applying Data Analytics to Real-world Scenarios
• - Project Planning, Data Acquisition, Analysis, and Visualization
• - Presenting Findings and Insights
• - Peer Review and Feedback on Projects