Certification Program in

Data Analytics

With

Microsoft

Eligibility

Undergraduates

Application deadline

November 23, 2024

Business Analytics Insights

About this program

Comprehensive Learning Path

Case-Based and Interactive Learning

Industry-Standard Tools & Technologies

120+ Hours of Live Learning

8+ Industry-Level Projects

Overview
Curriculum
Certification
Reviews
Pricing
FAQ

Our recipe for your success

Batch starts

November 2024

Duration

5 months

Learning Hours

200+ hrs

Comprehensive Learning Path

Case-Based and Interactive Learning

Industry-Standard Tools & Technologies

120+ Hours of Live Learning

8+ Industry-Level Projects

Practical Exposure and Masterclasses

Doubt Resolution and Peer Support

Generative AI for Data Analytics

Experience the difference with live learning

Real time engagement withlive classes

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Learn at your pace, on your schedule

Enhanced outcomes through more than 80% live and experiential learning

Our holistic learning philosophy

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Live learning

Live learning

Interactive classes with industry experts for hands-on learning

Case studies

Case studies

Real-world tasks to solidify knowledge and prep for industry challenges.

1:1 counselling

1:1 counselling

Personalized mentorship for career navigation and professional decisions.

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Seasoned faculty

Seasoned faculty

Guidance from leading industry experts to ensure top-tier learning.

Capstone projects

Capstone projects

Final projects that blend learning with real impact in your field.

Doubt clearing sessions

Doubt clearing sessions

Targeted sessions to ensure clarity and readiness for next steps.

Curriculum

Self-paced: Introduction to Analytics

  • What is Analytics
  • Why Analytics
  • Types of Analytics: Descriptive, Diagnostic, Predictive, and Prescriptive
  • Data and Data Sources for Analytics: Small Data, Big Data, Traditional Data and Non-Traditional Data Sources
  • Analytics in Business
  • Introduction to Problem Solving using Data
  • Managing Analytics Projects: CRISP-DM
  • Analytics Tools: What Tools to Use for which Type of Problems
  • Installation and Set-up, IDE, etc.
  • Python Basics: Syntactics, Variable types, Operators, For/While Loops, Conditional Statements
  • Functions: Built-in, Library and Custom, Arguments, Return
  • Data Structures and Operations: Lists, Tuple
  • Data Structures and Operations: Dictionaries, Sets
  • Implement nested loops and control mechanisms (break, continue, pass)
  • Create and use lambda functions for concise data processing
  • Combine loops and lambda functions for efficient data manipulation
  • File Handling: i/o functions, open(), read, write, append
  • More focus on CSV files
  • Linear Algebra: Vectors, Matrices
  • Calculus: Differentiation, Integration
  • Probability and Statistics: Mean, Median, Mode, Variance, Standard Deviation
  • Navigation and Shortcuts, Cells and Ranges, Entering Data, Applying Filters, and Formatting
  • Data Handling Using Functions: if-else, Concat, Deduplication, Missing Value Imputation, etc.
  • Data Summarizing using Functions: Countif, Sumif, Sumproduct, iferror, Average, Correlation, etc.
  • Visualization: Basic Charts/Graphs/Tables and related Customizations
  • Lookup Functions: vlookup (exact and approx), hlookup (exact and approx), Match, Index, Advanced Sort and Filter, Advanced Charting
  • Text Functions: Right, Left, Mid, Concatenate, Upper, Lower, Proper, Len
  • Date Functions: Datevalue, Timevalue, Today, Now, Networkdays, Networkdays.intl
  • Data Forecast, Data Consolidation
  • Pivot Tables: Create Table, Grouping, Slicer
  • Data Security, what-if analysis, and Data Validation
  • Record and Play Macro
  • Cell Reference
  • Copy Paste
  • Variable
  • Loops-for, do while, do until
  • if-if else, if elseif else, if elseif else with and operator, if else using for loop, select case
  • Userform-message box, input box, command button, radio button
  • Set up and install SQL-related software on your local machine
  • Examine why SQL databases are a preferred choice for storing data
  • Explain the need for a client-server architecture in a database server
  • Appreciate why SQL is used as a query language to pull data from a database
  • Fetch data from one or some columns in a table
  • Use the WHERE clause to filter subsets of data
  • Use ORDER BY clause to sort data
  • Use GROUP BY clause with aggregations to summarize data
  • Use GROUP BY with HAVING Clause to filter grouped data
  • Use CASE statements to write conditional logic like IF ELSE statements
  • Work with DATE functions to perform date related operations
  • Create Databases and Tables
  • Use INSERT command to add rows to the table
  • Use SQL Data Definition Language Statements to define the database structure or schema
  • Use Data Manipulation Language Statements to manage data within objects
  • Establish relationships in data to combine data from different tables
  • Analyze data after combining two or more tables using JOINS
  • Get insights on data using nested queries
  • Establish relationships in data to combine data from different tables
  • Analyze data after combining two or more tables using JOINS
  • Get insights on data using nested queries
  • Implement Windows Analytic function in Data Science
  • Analyze the usage of the OVER clause with PARTITION FRAME and ORDER FRAME
  • Use Aggregate, Ranking, and Windows Analytical Functions for analysis and insights
  • Data manipulation over excel from SQL
  • Introduction to Pandas and NumPy Modules
  • Pandas Basics: Data File Handling, Row/Columns Handling, Slicing, Drop, Sort, New Variable Creation, Observing Frequency Count
  • Pandas Advanced: Multiple Datasets Handling, Merge/Append, Multivariable GROUP BY/crosstab summaries
  • Working with Datetime Series Data, Dataframe
  • Working with Indexes and Multi-level Indexing
  • Dashboard Making
  • Central Tendency: Mean (Arithmetic, Weighted and Geometric), Median, Mode
  • Dispersion: Ranges, Variance, and Standard Deviation
  • Importance of Visualizing Data through Charts
  • Types of Charts and their Best Uses
  • Basics of Visualization in Python using Matplotlib and Seaborn
  • Components of a Plot, Subplots, Functionalities of a Plot
  • Plotting Data Distributions, Univariate Distributions, and Bivariate Plots
  • Binomial
  • Poisson
  • Chi-Square
  • Hypothesis Testing
  • Hypothesis Testing in the Industry for Statistical Testing
  • Core Statistical Concepts: p-value and Others
  • One/two way ANOVA
  • T tests
  • Chi Square
  • Non Parametric
  • Probability Basics: Definition of Probability, Mutually Exclusive Events, Independent Events, Relative Frequency
  • Idea of Distributions: Discrete and Continuous
  • Computing Distributions from Data and Deriving Insights
  • Apply filters on columns to restrict the data and display charts
  • Create various charts to present a Power BI report
  • Perform joins and relationships to calculate and display correct information in reports
  • Develop advanced DAX measurements and computed columns for advanced computations
  • Use graphics like column, line, pie, combination, scatter, treemap, funnel, gauges, and others to present data
  • Clean up messy data, model it as per the need, and then format the report to make a professional presentation
  • Make sophisticated reporting tables and matrices
  • Convey a story through visuals, turn data to provide insights, and data into interactive visuals
  • Discover how to use advanced features such as the report page, tooltips, and bookmarks in the data visualization process
  • Explore basics of storytelling and ABT framework
  • Create stories from data
  • Build good data presentation
  • Make a meaningful data visualization using appropriate charts
  • Deliver data storytelling
  • Complete Analytics project where data needs to be cleaned, processed, stored, analysed and visualized
  • Business Analytics Methods (SWOT, PESTLE, Value Chain, etc.)
  • Predictive Analytics (Forecasting Techniques)
  • Prescriptive Analytics (Optimization, Decision Making)
  • Sensitivity Analysis
  • Business Process Improvement and Data-Driven Decision Making
  • Case Studies in Business Analytics
  • Analysis through ChatGpt
  • Create Python Code through ChatGPT
  • Big Data analytics through Gemini
  • Introduction to Agile Methodologies
  • Agile Frameworks
  • Agile in Data Analytics
  • Project Initiation and Planning
  • Execution and Delivery
  • Collaboration and Communication
  • Monitoring and Adapting
  • Challenges and Best Practices
  • Discussion on Capstone
Business Analytics Insights

Unlock valuable insights

5-star rating by 97% of students.

Discover the outcomes of the program.

Explore the custom-curated learning path.

Master industry-relevant tools

Excel
Power BI
Sql
Chatgpt
Gemini
python
Numpy
Matplotlib
Pandas
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Launch projects, leap forward

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Hero Fincorp Loan Optimization and Risk Management Initiative

Analyze loan portfolios to improve risk management strategies using SQL, Power BI, and Excel. Identify high-risk loans, streamline approval processes, and enhance financial outcomes through data-driven insights, improving creditworthiness evaluations and decision-making frameworks.

Reducing Machine Downtime at Tesla with Predictive Maintenance

Reducing Machine Downtime at Tesla with Predictive Maintenance

Utilize advanced data analytics to predict machine breakdowns and recommend proactive maintenance schedules. Use SQL and Power BI to enhance operational efficiency, reduce repair costs, increase equipment lifespan, and ensure seamless Tesla operations.

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Herovired Certificate

Get certified

On successful completion of the program, you will be eligible for the Hero Vired certificate that places you in an elite league of professionals.

* Certificates are indicative and subject to change

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Our faculty, your mentors

Shakul Malik

Shakul Malik

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Faculty, Hero Vired | 10+ Years

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Shakul Malik, a Senior Faculty at Hero Vired, specializes in Python, HTML, CSS, Java, JavaScript, Spring Boot, Docker, Jenkins, and web security. With a Master's in CS from Maharishi Dayanand University, she has also worked with Primed Talent and TCS, delivering full stack development training.

Education

BSc. in Computer Science , Computer Science from MDU

Master’s in Computer Science , Computer Science from MDU

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Upendra

Upendra

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Associate Faculty, Data Science| 15+ Years

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Upendra Kumar Tiwari is a Data Scientist specializing in Machine Learning, Data Visualization, NLP, and Financial Analytics, with over 15 years of experience. Currently, he works at Synergistic Compusoft Pvt Ltd, focusing on data analysis and corporate training. Upendra is skilled in deep learning and analytical techniques and is committed to continuous learning and sharing knowledge.

Education

M.Tech from Mahamaya Technical University (formerly UPTU)

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Personalized career mentorship

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CV and LinkedIn profile building

Enhance personal branding, fostering better discovery and shortlisting.

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Interview preparation

Equipping candidates with the right skills and confidence to crack interviews.

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1:1 Career coaching sessions

Personalized mentoring to empower individuals to chart their professional journey.

Start your learning journey, today

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Certification Program in

Data Analytics

With

Microsoft

EMI Starts at

₹4,100/ month

Price: ₹99,000 + GST

What you will get:

Comprehensive Learning Path

Case-Based and Interactive Learning

Industry-Standard Tools & Technologies

120+ Hours of Live Learning

8+ Industry-Level Projects

Practical Exposure and Masterclasses

Doubt Resolution and Peer Support

Generative AI for Data Analytics

Duration

5 Months

Apply by

November 23, 2024

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Hero Vired is a leading LearnTech company dedicated to offering cutting-edge programs in collaboration with top-tier global institutions. As part of the esteemed Hero Group, we are committed to revolutionizing the skill development landscape in India. Our programs, delivered by industry experts, are designed to empower professionals and students with the skills they need to thrive in today’s competitive job market.
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