Internet is growing exponentially and so are businesses. Doing business in the era of digitisation is easy but making its strategy, analysing the data, forecasting the future, comparative analysis with the competitors' reports is not a layman's task. So why spend crores of rupees and sleepless nights evaluating all. Use Data Science get the work done at a lesser cost and smaller duration.
From fraud detection to weather forecasting, company's decision making to forecasting the future, everything is Data Science' game.
This is a combination of maths and programming, advanced analytics, Artificial Intelligence and Machine Learning which makes the calculations and forecasts readily available for the end users.
Learn Big Data, AI and ML under one umbrella i.e Data Science and become a Data Scientist.
AI and ML: Artificial Intelligence and Machine Learning is the new future.
No Technical Background Required: You must need not be a scientist or an engineer to learn the Data Science. Anyone can become the Data Scientist, who wants to foresee the future.
High Market Demand: Data Scientist' job is one of the most demanded and is highly paid jobs in the industry. Almost all the sectors of the industry uses it.
WHY REPL?
Life time validity (enroll one time and revise many times)
Interaction with the best faculty and Industry Experts
Small Batches to focus on each student
We focus on both theoretical and practical approaches in a parallel way.
You will be given the opportunity to work on a live project.
Outdoor activities to boost your confidence.
Presentation in class by the students.
Our Key Features:
Good Quality Material Notes
Smart Classes Available
Online Test
Chapter wise Assignments
Offline And Online Classes
Recorded class on Rays App
Eminent faculties of the IT Industry( Amazon, Wal-Mart, Oracle, Microsoft..)
Charts & Filters: Charts, filters, sort and slicers, Pivot tables and pivot charts
Introduction to Matplotlib
Basic Plotting with Matplotlib
Different Types of Plots
Advanced Plot Customization
3D Plotting
Working with Images
Animations
Integration with Pandas and NumPy
Introduction to Seaborn
Seaborn Plots
Customizing Plots
Statistical
Estimation and Visualization
Data Exploration and Analysis
Advanced Visualization Techniques
Working with Time Series Data
Integration with Pandas and NumPy
Introduction to Power BI: Overview of Power BI and its components, Installation and setup, Understanding the Power BI ecosystem, Importing data into Power BI
Introducing Microsoft Power BI Desktop: Introduction to Microsoft power BI Desktop, Downloading the Microsoft Power BI Desktop, Power BI Desktop interface and workflow
Connecting & Shaping Data: Power BI Front-End vs. Back-End, Types of Data Connectors, The Power Query Editor, Basic Table Transformations, Connecting to a Database, Extracting Data from the Web, Profiling Tools (Text Tools, Numerical Tools, Date & Time Tools), Change Type with Locale, Index, Conditional Columns and Calculated Column, Grouping & Aggregating, Pivoting & Unpivoting, Queries (Merging, appending, refreshing), Data Source Settings, Importing Excel model
Creating a Data Model: Data Modeling, Database Normalization, Fact & Dimension tables, Primary & Foreign Keys, Relationships vs. Merged Tables, Creating, managing & editing Table Relationships, Star & Snowflake Schemas, Connecting Multiple Fact Tables, Filter Context & Filter Flow, Model Layouts, Data Formats & Categories, Creating Hierarchies
Calculated fields with DAX: Data Analysis Expressions, DAX vs. M Languages, Intro to DAX Calculated Columns, Intro to DAX Measures, Implicit vs. Explicit Measures, Types of Measures (Quick Measures, Dedicated Measure Tables), Understanding Filter Context, DAX Syntax & Operators, Common DAX Function Categories: Basic Math & Stats Functions, Counting Functions, Conditional & Logical Functions, The SWITCH Function, Common Text Functions, Basic Date & Time Functions, Calculate Function, All Function, Filter Function, Iterator Function, Joining Data with RELATED, DAX Measure Totals, Time Intelligence Patterns
Visualizing data with Reports: Dashboard Design Framework, Sketching the dashboard layout, Adding Report Pages & Objects, Naming & Grouping Objects, Cards (Multi-Row cards, KPI Cards, Top N Text Cards), Charts (Building Charts, Formatting Charts, Line Charts, Bar & Donut Charts, Gauge Charts, Area Charts), Trend Lines & Forecasts, Visuals (Table Visuals, Matrix Visuals, Map visuals, Importing Custom Visuals), Filterting (Basic Filtering Options, Top N Filtering), Formatting (Conditional formatting, Advanced Conditional Formatting), Parameters (Numeric Range Parameters, Fields Parameters), Slicers (Report Slicers, Slicer Panels), Drill Up & Drill Down, Editing Report Interactions, Adding Bookmarks, Custom Navigation Buttons, Managing & Viewing Roles, Mobile Layouts
Power BI optimization tools: The Optimize Ribbon, Pausing Visuals, Optimization Presets, Applying All Slicers, Performance Analyzer, External Tools, Troubleshooting common issues in Power BI
Real-world Projects and Case Studies: Hands-on projects using real-world datasets, Analyzing and visualizing data to derive actionable insights, Presenting analysis findings effectively