Data Analytics Course
Statistical Modelling, Tools and Visualization to Extract Information from Data
Languages and Tools covered
Online (Discount Price)
₹50,000 ₹35000/*
(Inc 30% Discount)
- Online Training Program
Offline (Discount Price)
₹57,500 ₹40000/*
(Inc 30% Discount)
- Classroom Training Program
- 16 Weeks, 44 Sessions Program
- 5 Projects
- Hybrid Learning Model
- Certification Program
- Internship Included
- Job Placement Assistance
- Hackathon with Certification
- Regular or Weekend Batches
Get FREE 1:1 Counselling
Business Statistics
This module introduces the foundational concepts of business statistics, equipping students with the skills needed to analyze and interpret data for informed business decision-making. Students will gain a comprehensive understanding of both descriptive and inferential statistics and their applications in business contexts.
Descriptive Statistics
+
- Data vs Information vs Insight
- Introduction to Business Statistics
- Data Representation
- Measures of Central Tendency (Mean, Median, Mode)
- Measures of Distribution
- Normal Distribution
- Measures of Dispersion (Variance, SD)
- Measures of Position (Deciles, Percentiles, Quartiles, etc.)
- Standardization, Covariance, Correlation, Regression
Inferential Statistics
+
- Introduction to Probability
- Measuring Probability
- Types of Probability
- Law of Large Numbers
- Bayes Theorem
- Sampling Techniques
- Central Limit Theorem
- Hypothesis Testing, Confidence Interval, p-value, Significance Level
- Type I & II Errors
- t-test, z-test, Chi-Square, ANOVA
Advanced Excel for Analytics
This module delves into the advanced features and capabilities of Excel, empowering students to perform sophisticated data analysis and make data-driven decisions. Students will learn how to manage and analyze data efficiently using advanced Excel functions and tools.
Advanced Excel
+
- Getting Started with Excel, Introduction, Toolbar
- Formatting in Excel, Formula Tab, Essential Formulae
- Functions in Excel, Errors & Handling
- Conditional Statements, String Handling, Statistical Functions
- Date & Time Functions, LOOKUP in Excel
- Data Toolbar, Advanced Analytics Tool Pack
- Crosstab Analysis & Pivoting
- Macros in Excel, Editing & Referencing, Data Protection
- Visualization using Excel
MIS Reporting
+
- Basics of Management Information Systems
- MIS Techniques, Tools for MIS
- Creating Reports and Dashboards using Excel
- Auto-referencing, Updates, Publishing Reports
Database Concepts & MySQL
This module provides a comprehensive introduction to relational databases, which are fundamental to organizing and managing data in many modern applications. Students will learn the principles of relational database design, querying, and management, enabling them to store, retrieve, and manipulate data efficiently.
Relational Databases
+
- Introduction to Data & Databases
- Understanding Relational Databases
- Data Storing, DBMS, Schema
- Queries, Indexes, and Security
- Types of Databases
SQL
+
- Introduction to SQL, Data Structure, Basic Commands
- Data Querying, Constraints, Functions, Manipulation
- Data Definition, Installing MySQL, Setting up MySQL Server
- DDL, DML, DQL, TCL, DCL
- Joins, Union, Union All, Views, Aggregating Data
- Sub Queries, Window Functions
- Stored Procedures, Exception Handling, Triggers, Common Table Expression
Python with Libraries
This module covers the essential fundamentals of Python programming. Starting from the basics of Python syntax and progressing through key concepts such as sequences, conditional statements, and control loops. Students will gain a solid foundation in Python, enabling them to write and understand simple to moderately complex programs.
Introduction to Python
+
- Programming Basics using Python
- Scientific & Numerical Computing
- Algorithm Thinking, and Flow Charting
- Python IDE, Jupyter Notebook, VS Code
- Expressions, Indentation, Keywords, Identifiers
- Variables, Comments, Type Casting, Data Types
- input() & print(), Types of Operators
Advanced Python Concepts
+
- Random Module, Zip, Functions (Default & User-Defined)
- Parameters vs. Arguments, Lambda, map, reduce, filter
- Namespaces, Scope of Variables
- OOP Concepts, Inheritance, Polymorphism, Multithreading
- Exception Handling, Try & Except, finally & raise
- NumPy Library, Pandas Library
Visualization in Python
+
- Basics of Data Visualization
- Matplotlib for Data Storytelling: Different charts/plots
- Seaborn for Data Storytelling: Different charts, Styling
Exploratory Data Analysis (EDA)
This module provides a comprehensive overview of Exploratory Data Analysis (EDA) techniques, crucial for understanding and preparing data for further analysis. Students will learn both qualitative and quantitative methods for examining data, along with essential skills in data profiling and management.
Exploratory Data Analysis (EDA)
+
- Data Loading from Multiple Sources
- Data Analysis, Management, Aggregation, Correlation Analysis
- Date & Time methods, Analyzing Real-time Data
- Applying Visualization, Insight Generation, and Reporting
Feature Engineering
+
- Understanding Features, Feature Selection
- Creating, Extraction, Encoding, Scaling, and Transformation Techniques
- Data Preprocessing for Analysis & ML
Time Series Analysis
+
- Understanding Time Series, Metrics & Events, Analysis
- Auto Regression (AR), Auto Correlation, Moving Average Method
- Stationarity of Time Series, ARIMA, and ML for Time Series
Power BI
This module provides an in-depth exploration of Power BI, a powerful business analytics tool. Students will learn how to use Power BI to transform raw data into meaningful insights through interactive dashboards and reports.
Exploring Power BI
+
- Introduction, Installation, Parts: Desktop, Service, Mobile apps
- Power BI Workflow, Importing Data: Loading data from different sources
- Power Query Editor, Data source connectivity
Advanced Power BI
+
- Data Cleaning and Transformation, Data shaping
- Query Dependencies, Parameters, M Language
- Data Transformations: Cleaning, Filtering, Sorting, Aggregating, Reshaping, Joining, Splitting
- Deriving calculated fields, Handling Time Series, Modeling, Relations between tables
- Analytical Queries with DAX: Columns, Measures, Aggregation, Math, Logical, Relationship, Filter
- Information, Table Manipulation, Text DAX Functions, DAX Query Tools
- Time Intelligence: Functions, Reports with time intelligence
- Visualizations with data points, Buttons, Bookmark, Drill-through, Applying filters
- Publishing reports into Service, Multi-page, Simple to Complex
- Row Level Security
Tableau for Business Intelligence and Data Analytics
This course offers a comprehensive introduction to Tableau, a powerful tool for business intelligence and data visualization. Students will learn to effectively load, transform, and model data within Tableau, enabling them to create insightful and interactive visualizations.
Foundations of Tableau
+
- Installation, Tableau vs. Power BI
- Components, MDX functions, Parameters, calculated fields
- Geographic & Time Series, Visualizations
- Dashboard and Stories, Publishing
Introduction to Machine Learning
This course provides a foundational overview of machine learning, covering key concepts, techniques, and applications. Students will learn about different types of machine learning, including supervised, unsupervised, and reinforcement learning.
Essentials of Machine Learning
+
- Exploring ML, Supervised vs. Unsupervised
- Data Pre-processing vs. Accuracy, Classification vs. Clustering
- Architecture of ML, Training & Testing Data, Hyperplane
Linear Regression
+
- Simple, Multiple & Polynomials, Lasso
- Model Training & Evaluation Metrics
- Understanding Errors (SSE, SSR, SST, MSE)
- R-Square, Adj. R Square, RMSE, OLS Method, Cost Function, Gradient Descent
Classification - Logistic Regression
+
- Logistic Regression, Log Odds, Model Optimization
- Confusion Matrix, Bias & Variance
Reporting & Dashboarding
This module provides an in-depth understanding of dashboard reporting, offering a visual representation of key performance indicators (KPIs). Students will learn to create and refine dashboards for real-time data analysis and strategic reporting.
Essentials
+
- Requirement Analysis, Objective identification
- Data Gathering & Representation, Data Integration
- Stakeholder Identification, Resource Planning, Tool Analysis
- Project Management, Delivery guidelines
Report Generation
+
- Structured and Unstructured data, Layout finalization
- Selecting graphs and charts, Data Analysis, Shortfall identification
- Data Sufficiency, Visualization, Presentation
- Operational Reports, Analytical Reports, Strategic Reports
- Insights to key metrics and trends, Summary writing
Dashboarding
+
- Single and Multi-form designs, Connecting Databases
- Dynamic reports, Visual Representation, Real-time data analysis
- Customization, Accessibility, Publishing
- Operational and Analytical Dashboards
- Testing and Refining, Deployment and Monitoring
Real-time Projects
Curriculum
The Curriculum supports step-by-step transformation while building confidence to handle various domain problems.
44 Sessions
Learning content
15+
Languages & Tools
WhyData Analytics
Data Analytics is crucial for making informed managerial decisions by analyzing and extracting insights from data. As data volumes grow, businesses increasingly rely on these insights. The best part? It’s accessible to non-technical professionals and serves as an excellent entry point into Data Science.
- Statistical Models:
- Data Analytics utilizes statistical models to analyze data and generate actionable insights, which are critical for making informed business decisions.
- Visualization Techniques:
- By using visualization techniques, Data Analytics helps present complex data in an easily understandable format, aiding stakeholders in interpreting data effectively.
- No Coding Required:
- One of the key advantages of Data Analytics is that it typically does not require coding skills, making it accessible to professionals from diverse educational backgrounds.
Project Base Learning
MASTER FROM DATA SOURCING TO MODEL BUILDING
Your Pathway to Mastery
Data Analytics Learning Path
A comprehensive roadmap to becoming job-ready in Data Anaytics.
- Python Pre-Videos
- Learn before attending sessions.
- Offline / Online Session
- Choose your favorite mode of learning.
- Recorded Sessions
- In case you missed sessions or need a re-run.
- Jupyter Notebooks
- Download code and notes as needed.
- Assignments
- Convert theoretical knowledge into skills.
- Periodical Assessments
- Self-test to identify gaps & seek support.
- Projects - Mini & Major
- Showcase your skills through project-based learning.
- Interview Preparation
- 100s of questions & answers for practice.
- Final Assessment
- Thorough assessment to identify gaps.
- Job Readiness
- Mock interviews, CV prep, projects, HR / expect rounds, and more.
Course Information
If you are thinking about a Data Analytics course you are ready to step into the world of Data Science. This course emphasises Statistical Modelling, various Applications or Tools, Visualization, Dashboarding and such. Students from any background could learn this course and become job-ready. They could solve the business problems using Data Analytics techniques to enable regular business decision processes. Post completion of the course you would be ready to work with an organization as part of their analytics team.
All-in-one Data Analytics Program
Our Data Analytics course offers comprehensive training designed to equip you with the skills needed to excel in the industry. With our job-ready curriculum, hands-on projects, and hybrid learning model, you'll be well-prepared for a successful career in Data Analytics.
- Easy to learn and Job-ready program
- The curriculum is designed for easy learning and focuses on preparing you for job readiness in the Data Analytics field.
- No coding involved
- You can start learning Data Analytics without any prior coding knowledge, making it accessible to everyone.
- Hybrid Learning Model
- Experience a blend of online and offline learning for effective knowledge transfer and flexible learning opportunities.
- Minimum Batch Size
- Enjoy personalized attention with our small batch sizes, ensuring that each student gets the guidance they need.
- Job Preparation with Profile building
- Get job-ready with expert guidance on resume building, mock interviews, and portfolio development.
- Internships and projects
- Gain hands-on experience with internships and real-world projects, boosting your practical skills and employability.
- Scholarship Assessments
- Avail of scholarships by taking assessments designed to help you finance your education and reduce your course fees.
Course Highlights
If you're preparing to enhance your skills and knowledge. Our courses emphasize foundational learning, practical implementation through projects, and real-world experience, ensuring you are well-prepared for the challenges of your chosen field. From engaging hybrid learning sessions to hands-on internships, our comprehensive approach is designed to build your confidence and transform your expertise into career-ready skills.
Prepare
Foundation courses designed to bring you up to the speed, irrespective of your background.
Learn
Hybrid Learning to engage learners even before the class for effective knowledge transfer.
Implement
Project-Based Learning for confidence building and transferring knowledge into skills.
Experience
Internships & Job Readiness to give real-time experience and prepare for interviews.
Jobs for a Data Analyst
Data Analyst professionals are currently in high demand due to the high dependency on data-centric decisions. This is the right time for anyone to step into the world of Data Analytics through this course. The demand is increasing one yearly basis. With right skills and knowhow, you could be a hot cake in the market. Organizations are looking for professionals with good data skills, visualization, and analysis to work in their teams. It give opportunity to grow within the organization and also to become a Data Scientist.
Contact us
Get in Touch With Us
- Phone number
- 8977944952/53
- hello@cedlearn.com
- DELHI
HYDERABAD
KOCHI
BANGLORE
Business Hours :
Monday - Saturday: 9:00a.m to 8:00p.m
Sunday: With Appointment Only
Send a Message
Write to us. We would catch up with you as soon as we receive your message
scholarship & discounts
We believe in encouraging talented learners with Scholarships to avoid the learning hurdles due to financial limitations. However scholarships must be awarded based on the merit and hence our assessments. We would be glad to assess learners using our multi-dimensional assessment to identify the dormant potential and thus encourage them through the learning process by offering financial benefits. To know more you could contact us or register for the online assessment. If you are not clear on the career path in the field of AI, please feel free to meet our career counsellor. We would be glad to guide you through the career options to draft a personalized career path.