Generative AI  /  Beginner to Mastery

Data Analytics Course

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Course Duration

300 Hours

 

Course Material

Live. Online. Interactive.

Opens doors to diverse roles in data analysis, business intelligence, and analytics.

Offers skills that are applicable across various industries and roles.

Keeps you updated with the latest technologies and industry trends.

Opens doors to diverse roles in data and analytics.

KEY HIGHLIGHTS OF DATA ANALYTICS COURSE PROGRAM

1) Weekly sessions with industry professionals

2) Dedicated Learning Management Team

3) 300 hours of hands-on learning experience

4) 90+ Live Sessions Across 4 months

5) 90 Hours of Self-Paced Learning

6) Learn from Industry Experts.

🔺More than 25+ industry-related projects and case studies

🔺24*7 Support

🔺1:1 Mock Interview

🔺Designed for both working professionals and fresh graduates

🔺Competitive Edge and Innovation

🔺 One-on-One with Industry Mentors

🔺Dedicated Learning Management Team

🔺No-Cost EMI Option

🔺High Demand and Career Opportunities

🔺Problem-Solving and Critical Thinking

WHY JOIN DATA ANALYTICS COURSE?

Comprehensive Coverage

Master a wide range of essential tools and techniques, from data analytics to advanced data visualization and statistical analysis.

Industry-Relevant Skills

Acquire highly in-demand skills that boost your employability in today’s competitive job market.

Career Growth

Unlock advanced career opportunities and elevate your earning potential in data analytics, business intelligence, and related fields.

Hands-On Learning

Implement your knowledge through practical projects and real-world case studies focused on data analytics.

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Data Analytics Course OVERVIEW

This program helps participants become proficient in data analysis. It includes Advanced Excel, Python, Statistics, SQL, and data visualization using Tableau. By mastering these skills, participants will gain a strong foundation in data management, analytics, and visualization techniques, empowering them to turn raw data into actionable insights.

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Data Analytics Course Objectives

The program is aimed at offering essential knowledge in key areas related to data analysis, Python programming, and statistical techniques useful for data-driven decision-making. It emphasizes SQL for database management and Tableau for data visualization. The course is designed to make participants well-versed in data analytics, equipping them with the skills needed to analyze data and generate actionable insights.

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                                             Why Learn Data Analytics Course? 

MASTERING IN PAYTHON & DATA ANALYSIS

Gain proficiency in R, statistical analysis, and data visualization to effectively explore and understand data.

ADVANCED EXCEL & SQL SKILLS

Develop strong capabilities in data manipulation, database management, and querying using Excel and SQL.

DATA VISUALIZATION WITH TABLEAU

Learn to create compelling visual reports and dashboards to communicate insights effectively.

INDUSTRY-RELEVANT TOOLS

Get trained in widely used tools and technologies that align with current market needs.

CAREER GROWTH OPPORTUNITIES

Equip yourself with skills that open pathways to roles such as Data Analyst, Business Analyst, and BI Specialist.

ENHANCE COMMUNICATION

Effectively convey complex information and findings using data visualization techniques.

DRIVE DATA-DRIVEN DECISION MAKING

Leverage analytical skills to contribute to the development of data-driven solutions and insights.

HANDS-ON PROJECTS

Apply your skills in real-world projects to gain practical experience and build a robust portfolio.

Program Advantages

✅ Master essential tools like Advanced Excel, Statistics, Python, SQL & Tableau .

✅ Learn up-to-date practices that match current market demands in data analysis.

✅ Apply knowledge through real-world projects and hands-on exercises for practical experience.

✅ Equip yourself with versatile skills applicable across various industries and sectors.

✅ Develop data visualization expertise to effectively communicate insights and drive decision-making.

✅ Stay ahead with in-demand tools that shape the future of data analytics.

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Data Analytics Course Certifications

Data Analytics Course Curriculum

Module 01 - Advanced Excel
Lecture 01: Orientation (Introduction to Data Science, Scope of Data Science)
Lecture 02: Microsoft Excel Overview, Basic Navigation and Usage, Cell Referencing, Formatting Excel, Advanced Formatting, Shortcuts and Basic Formulas
Lecture 03: Sorting, Filtering, Advanced Filtering, Charts, Types of Charts, Advanced Charting Techniques, and Pivot Tables (Creating, Grouping and Summarizing Data)
Lecture 04: Lookup Functions, VLOOKUP, Using VLOOKUP with Multiple Criteria, HLOOKUP, Combining HLOOKUP with Other Functions, MATCH Function, Using MATCH for Dynamic Referencing
Lecture 05: Introduction to VBA & Macros, Understanding VBA Basics, Debugging and Error Handling, Advanced VBA Techniques, Integrating VBA with Excel Functions, Designing Effective Dashboards, Building a Dashboard
Lecture 06: Introduction to dplyr, Selecting, filtering, and arranging data, Grouping data, Summarizing data with summarize and mutate
Lecture 07: Advanced Data Analysis Techniques, DAX, Scenario and Sensitivity Analysis, Dashboards and Reports, Case Studies and Real-World Applications, Practical Examples of Data Analysis in Excel
Module 02 - Python
Lecture 08:  Introduction to Python, Why Python, Variables, Data Types, Type Casting, Strings, Indexing
Lecture 09: Operators and Conditional Statements, Looping Statements and its Control Statement
Lecture 10: Lambda Functions, *args, **kwargs, Functions
Lecture 11: Data Structures – List, Tuple, and List Comprehensions
Lecture 12: Data Structures – Set and Dictionaries
Lecture 13: Classes, Objects and Constructors, Inheritance
Lecture 14: Polymorphism, Abstraction and Encapsulation
Lecture 15: Connecting to Databases, Establishing Connections to Databases, Executing SQL Queries, ORM (Object-Relational Mapping), Working with NoSQL Databases
Lecture 16: Introduction to Numpy and Pandas
Lecture 17: Introduction to Seaborn and Matplotlib
Module 03 - Statistics
Lecture 18:  Introduction to Statistics, Descriptive Statistics, Sample, Population, Major of Central Tendency, Standard Deviation,
Lecture 19: Variance, Range, IQR, Outliers, Correlation, Covariance Skewness, Kurtosis, Probability
Lecture 20: Probability, Probability distributions, Central Limit Theorem, Binomial and Poisson Distribution
Lecture 21: Normal Distribution, Type I & Type II Error
Lecture 22: T-test, Z-test, Hypothesis Testing
Interview Questions

 

Module 04 - SQL
Lecture 23: Basics of Database, Types of Database, Data Types, SQL Operators, Expressions, Create, Insert
Lecture 24: Drop, Truncate, Delete, Alter, Update, Select, Range, Operator, IN, Wildcard, Like, Clause
Lecture 25: Constraint, Aggregation Function, Group By, Order By, Having
Lecture 26: Classification Report, AUC ROC, Accuracy, Ensemble Techniques, Random Forest, Xgboost
Lecture 27: Joins, Case, Complex Queries, Doubt Clearing
Module 05 - Tableau
Lecture 28:  Tableau Desktop, Tableau Products
Lecture 29: Data Import, Measures, Filters
Lecture 30: Data Transformation, Marks, Dual Axis
Lecture 31: Manage Worksheets, Data Visualization, Dashboarding
Lecture 32: Project Session

Data Analytics Course Skills Covered

Data Analytics Course Tools Covered

Data Analytics Course Benefits

Cutting-Edge Knowledge:

Stay ahead with the latest advancements in data analytics and visualization technologies.

Future Of Your Career

Unlock well paying high-demand jobs in the Data and tech industry.

Real-world Applications

Solve challenging problems in all competitive coding related domains.

Comprehensive Learning

Gain a holistic understanding of data analytics, from foundational concepts to advanced techniques.

Career Growth

Enhance your employability in a rapidly evolving and high-demand field.

Earn Certification

Earn a certification that validates your expertise and enhances your professional credibility.

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Admission Process

The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.