AnalyticsData Analytics Training
Turn data into decisions.
A complete data analytics program — Excel, SQL, Python, statistics, Power BI and Tableau — from the basics to advanced techniques, with real-life projects that become your portfolio.
Beginner friendly · talk to us about the next batch, schedule and fees
11Course modules
110+Topics
5 toolsExcel · SQL · Python · Power BI · Tableau
ProjectsReal-life datasets
Basics → advancedNo prior experience needed
InterviewPreparation included
Your analytics skill pathtap a skill
Each skill opens the matching modules in the curriculum below.
Tools you’ll master
Microsoft ExcelPower QuerySQLMySQLPythonpandasNumPyStatisticsPower BIDAXTableau
Why this program
Everything a data analyst uses at work.
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The full analyst toolkitExcel, SQL, Python, statistics, Power BI and Tableau in one program.
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Basics to advancedStart from zero — every topic is covered from the ground up.
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Real-life projectsWork on real datasets and build a portfolio employers can see.
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Dashboards that tell storiesTurn analysis into clear, interactive dashboards in Power BI and Tableau.
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Learn from a practitionerTaught by a data scientist and corporate trainer.
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Interview-readyAnalytics interview questions and practice built in.
Course curriculum
11 modules. 110+ topics.
- Excel essentials — formulas, functions and cell references
- Lookup functions — VLOOKUP, XLOOKUP, INDEX & MATCH
- Logical and text functions for cleaning data
- Sorting, filtering and conditional formatting
- Pivot tables and pivot charts
- Power Query in Excel
- Building interactive Excel dashboards
- Introduction to Database
- Component of Database
- Types of Databases
- Relational Database,
- Object-Oriented Database,
- Distributed Database,
- NoSQL Database,
- Graph Database,
- Cloud Database,
- Centralization Database,
- Operational Database
- Vector Databases
- Introduction to Structured Query Language
- What is RDBMS-Relational Database Management System
- Introduction and Types of SQL Operators
- Creating Databases and Tables
- Explore Entities relationships
- DDL & DML Statement
- Select Statement, Aggregate Functions
- Insert into, Where, Order By, Distinct, Group By, Like, In, Between Operators,
- Limit Aliases, and & or Clause
- Update & Delete Query
- SQL Joins-What are Joins, Inner Join, Left Join, Right Join, Full Join
- Multiple Joins-Joining More than two tables
- Subqueries
- How to write Subqueries in SQL
- Conditional Table Expression
- Windows function in SQL
- Views, functions, and Stored Procedure
- Transactions
- String, transformation, regex
- Date time manipulation
- What is Python
- Identifiers and Keywords in Python
- Data Types & Type casting
- Basic Operation and Operator in Python
- Operators in Python
- Indentation, Statements and Comment
- Data Structures in Python — Array, String, Lists, Tuples, Set and Dictionaries
- Conditional statements in Python
- Loops in Python
- Function in Python
- Lambda functions
- Classes and OOPs concept
- Regular expression
- File handling
- Exception handling
- Command line Arguments
- Handling date and time
- Introduction to Data Science
- Data Science Lifecycle
- Types of Data
- Checking the quality of data
- Exploratory data analysis
- Feature Engineering
- Tabular Data Preprocessing
- Image Data Preprocessing
- Text Data Preprocessing
- Introduction to statistics
- Types of statistics
- Descriptive and Inferential
- Descriptive Statistics
- Variables and Types of Variables
- Measure of Center and Measure of Spread
- Measures of Central Tendency
- Measures of Dispersion
- Mean, Mode, Median
- Range, Standard Deviation, Variance, Quartile, IQR
- Covariance and Correlation between data
- Inferential Statistics
- Sample v/s Population
- Hypothesis Testing
- Null and Alternative hypotheses
- Type I error vs Type II error
- Establishing a rejection region and a significance level
- What is the p-value and why is it one of the most useful tools for statisticians
- Learning about T-test
- One Sample, two Sample T-test
- Analysis of Variance
- Chi-square Analysis
- Parametric and non-parametric tests
- Introduction to PowerBI
- Components of PowerBI
- Types of charts in PowerBI
- How to add buttons in PowerBI
- Using Power query to preprocess the data
- Intro to the M Language
- Data modelling in PowerBI
- How to write and run DAX queries
- How to create dashboard
- How to add security on the dashboard
- Publishing the dashboard
- Refreshing the dashboard periodically
- Introduction to Tableau and its interface
- Connecting to data sources
- Joins in Tableau
- Blending vs joining data in Tableau
- Calculated fields and table calculations
- Window functions in Tableau
- Time series analysis in Tableau
- Building dashboards and stories
- End-to-end analytics projects on real-life datasets
- From raw data to dashboard — cleaning, analysis and storytelling
- Presenting insights to stakeholders
- Building a portfolio of projects
- Analytics interview questions and practice
No topics match your search.
Who it’s for
For anyone who wants to work with data.
🎓Students and fresh graduates
🔁Career switchers into analytics
📈Business and finance professionals
🧾Excel users ready for SQL and BI
🛠️Engineers moving into data roles
💼Anyone preparing for data analyst interviews
Start learning free
Try our free tutorials first.
Meet your trainer
Connect on LinkedIn
Abhishek Kumar Singh
Data Scientist · Consultant · Corporate Trainer
8+ yrsData science, AI & big data
45+Corporate trainings delivered
Abhishek has trained professionals in Power BI, Tableau, SQL, Python, Excel and data science — including teams at leading organizations — with a teaching style learners describe as thorough, practical and tailored to real work.
Technology stack
Organizations trained
DeloitteGSKShellCapgeminiMetLifeTruistJP MorganWells FargoElevance Health
Reviews
What learners say about our data training.
I had the privilege of receiving exceptional training from Abhishek in various technical skills. His expertise spans a wide range, including Power BI, Tableau, SQL, Python, Excel, and Data Science. Abhishek’s teaching style is thorough, insightful, and tailored to practical applications. I highly recommend his training to anyone seeking to enhance their proficiency in these critical areas.
Dhiraj SinghFund Manager · Metlife
The instructor is friendly and supportive, providing valuable interview guidance and short notes for each class. The flexible schedule and hands-on projects enhance learning. Regular feedback and a focus on real-world applications built my confidence. Overall, it was a fantastic course that significantly improved my skills.
Kaushal GoreData Analyst
Abhishek was approachable and always ready to help. Students were provided helpful learning material for each class. The course content spanned a wide range of topics, from the basics to advanced concepts, ensuring a solid understanding of each area. It was well-structured and gave a comprehensive overview of various aspects of data science, making it an enriching learning experience. I would highly recommend this course to anyone looking to deepen their knowledge in data science.
Pavan KoutharapuML Engineer · Way2News
I recently completed the Data Science course, and I must say it was an outstanding experience. The course content was comprehensive and well-structured, covering all essential aspects of Data Science from fundamentals to advanced techniques. The instructor was highly knowledgeable and passionate about the subject, making complex concepts easy to understand through engaging lectures and practical examples. One aspect that particularly stood out was the hands-on approach to learning. The seminar provided ample opportunities for practical application of the concepts learned, through coding exercises, real-world case studies, and projects. This not only enhanced my understanding but also equipped me with valuable skills that are directly applicable in the field of Data Science. Furthermore, the support from the instructor was exceptional. He was always available to clarify doubts and provide guidance. Overall, I would highly recommend this course to anyone interested in Data Science. Whether you're a beginner looking to start your journey in this field or an experienced professional seeking to expand your knowledge, this seminar offers tremendous value and expertise.
Petros CholidisGenAI Engineer
I would highly recommend DataSpoof to anyone looking to get started in data science or expand their existing knowledge. I was thoroughly impressed with the quality of instruction and the level of detail provided throughout the course. The instructor was knowledgeable and engaging and was always available to answer questions and provide feedback.
Rabia NaveedStudent · Brunel University
Data Analytics Training
Join the next batch
11 modules across Excel, SQL, Python, statistics, Power BI and Tableau — with real-life projects and interview preparation.
Book a free demo → Ask about fees on WhatsAppWhat’s included
- Excel, SQL, Python, statistics, Power BI and Tableau
- Real-life projects for your portfolio
- Dashboards and data storytelling
- Analytics interview questions and practice
Questions before you join?
Ask about the schedule, fees or whether the program is right for you.
💬
Chat on WhatsApp+91 83182 38637
Fastest
🗓️Book a free demo30-minute call on Calendly
Free
✉️Email ussupport@dataspoof.in
Anytime
Want to go further into machine learning? See our Data Science Training.
No. The program covers everything from the basics to advanced techniques, starting with Excel and building up to SQL, Python and BI tools.
Data Analytics focuses on analysing data and communicating insights — Excel, SQL, Python, statistics, Power BI and Tableau. Data Science goes further into machine learning, deep learning, NLP, big data and MLOps.
Yes. You’ll work on real-life analytics projects — from raw data to finished dashboard — that you can add to your portfolio.
Book a free demo or message us on WhatsApp at +91 83182 38637 — we’ll share the schedule, fees and what’s included.
Start your analytics career
Make data your superpower.
Book a free demo to see how the classes work and get the next batch dates.