Data Analytics Course Description :

Our Data Analytics Course offers a comprehensive curriculum designed to equip participants with all the skills and knowledge required for excelling in the rapidly evolving world of data analytics. This certification program covers essential topics like data collection, cleaning, analysis and interpretation using cutting-edge methods and tools; students also gain hands-on experience through practical exercises and real world case studies to develop foundational as well as advanced techniques of data analytics.

Types of Data Analytics Covered:

Descriptive Analytics: This method synthesises historical data to gain insight into past performance.

Diagnostic Analytics: Examining data to understand why specific outcomes occurred.

Predictive Analytics: These analytics entail making predictions based on past patterns to predict future events or outcomes based on historical information.

Prescriptive Analytics: Recommending actions that optimize future results based on predictive insights.

Data Analytics Course in Delhi

Our Data Analytics Institute in Delhi learning environment features state-of-the-art facilities and expert faculty to facilitate an excellent data analytics education. The curriculum has been thoughtfully created for aspiring data analysts and professionals looking to advance their careers in data analytics. Participants will enjoy personalized mentorship services, industry projects that directly relate to data analytics careers, and placement assistance to start or advance in this high-demand industry.

Who is it for?

This data analytics certification is ideal for:

  • Aspiring Data Analysts: Individuals hoping to break into data analysis via comprehensive training.
  • Business Professionals: Looking to sharpen analytical abilities for strategic decision-making and operational efficiency purposes.
  • IT Professionals: who wish to switch into data analytics roles, or deepen their understanding of data science.
  • Researchers and Academics: who hope to integrate data analysis into their research methodologies and methodologies.
  • Graduates: Seeking to build an exceptional data analytics foundation as they advance in their careers.

Data Analytics Curriculum

Introduction to Advanced Excel
  • Overview of Excel for data analysis
  • Advanced functions and formulas
  • Data validation and conditional formatting
Data Analysis with Excel
  • PivotTables and PivotCharts
  • Advanced charting techniques
  • Data modeling and what-if analysis
Introduction to Databases and SQL
  • Relational database concepts
  • Basics of SQL: SELECT, WHERE, JOINs
  • SQL for data manipulation (INSERT, UPDATE, DELETE)
Advanced SQL
  • Subqueries and nested queries
  • Aggregation functions (GROUP BY, HAVING)
  • Data normalization and database design principles
Introduction to Power BI
  • Overview of Power BI tools and services
  • Connecting to data sources
  • Building basic reports and dashboards
Advanced Power BI
  • Data modeling in Power BI
  • DAX (Data Analysis Expressions) basics
  • Advanced visualization techniques and custom visuals
Introduction to Python
  • Basics of Python programming language
  • Data types, control structures, and functions
  • File handling and basic data manipulation with Python
Python for Data Analysis
  • Introduction to data science libraries (NumPy, Pandas)
  • Data cleaning, transformation, and manipulation
  • Introduction to data visualization with Matplotlib and Seaborn
NumPy
  • Arrays and matrices in NumPy
  • Basic operations and broadcasting
  • NumPy for statistical analysis
Pandas
  • Introduction to Pandas Series and DataFrame
  • Data manipulation and analysis with Pandas
  • Handling missing data and merging datasetss
Data Visualization with Matplotlib and Seaborn
  • Basic plotting with Matplotlib
  • Creating statistical plots with Seaborn
  • Customizing visualizations and adding annotations
Data Analytics Course Program Highlights
  • Introduction to Data Analytics: Overview, Importance, and Basic Concepts.
  • Statistics Analysis: Tools for summarizing and interpreting data, such as descriptive statistics or inferential methods.
  • Data Visualization: Tools and principles to effectively present data through graphs, charts, or dashboards.
  • Data Mining: Techniques for finding patterns and relationships within large datasets using algorithms and statistical techniques.
  • Machine Learning: Introduction to algorithms and models for predictive analytics and pattern recognition.
  • Database Administration: Skills needed for organizing, storing, and retrieving information using relational databases and SQL.
  • Big Data Technologies: Here is an overview of technologies and platforms for processing large data volumes.
  • Ethics and Privacy: Considerations when managing sensitive data ethically and legally.
  • Case Studies and Projects: Practical applications of data analytics techniques applied directly to real-world problems through individual or collaborative projects.
  • Industry Applications: Exploration of how data analytics is employed across various fields such as finance, healthcare, and marketing.
  • Emerging Trends in Data Analytics: Analysing new developments and trends in data analytics such as AI-powered or IoT data analytics.
  • Capstone Project: Concluding project in which students apply all learned data analytics skills to solve a vital data analytics challenge or issue.
About Data Analytics

The Data Analytics course offered by the Academy of Success aims to equip participants with all the skills and knowledge required to excel in the rapidly expanding data analytics industry. AOS is one of the premier institutes offering courses related to this sector with industry-relevant curriculums taught by expert faculty.

Participants begin by mastering foundational concepts of data analytics, such as types and sources, lifecycle, and advanced statistical techniques, and then apply both descriptive and inferential statistics techniques for data analysis to gain meaningful insight.

Practical skills in data wrangling and preprocessing will be emphasized during this workshop, teaching participants to effectively clean, transform, and prepare data for analysis using tools such as Python, R, SQL Server, or Tableau. Gaining such hands-on experience ensures efficient visualization and clear communication of findings from this training course to stakeholders.

This course covers predictive analytics and machine learning techniques for participants to build and evaluate predictive models using real-world datasets. Through practical projects and case studies, they gain experience applying these techniques to solve complex business issues while streamlining decision-making processes.

Ethics are at the core of AOS' curriculum for data analytics training courses. Participants learn about privacy regulations, ethical data practices, and upholding data security and integrity while conducting analyses.

AOS offers comprehensive career support beyond technical skills development. This includes workshops on resume building and interview preparation, networking events with industry professionals, and support to prepare graduates to begin successful careers as data analysts, data scientists, or business intelligence specialists in different sectors.

Overall, the Academy of Success's Data Analytics course blends theoretical understanding with practical application, equipping participants to effectively utilize data in our increasingly data-driven world and contribute to organizational success in this increasingly informational sphere.

Eligibility
  • 12th pass
  • Basic Computer Knowledge
Exam Details
  • Offline/Online Mode
Upcoming Batch
S.NO. AI Starting Batch
1 10th of every month
2 15th of every month
3 18th of every month