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Prime - Skill Mastery Pack
Instructor: LEO
Validity Period: Lifetime
₹10000
50 Edu Tantr Coins as Cashback
Description:
🌟 Comprehensive Learning: Gain access to 15+ beginner-friendly courses designed to provide hands-on experience and industrial certification for every course.
✨ Key Highlights:
- 🏅 Certification for every course.
- 🤝 Industry-relevant curriculum crafted by experts.
- 💻 Hands-on projects for real-world application.
- 🌐 Knowledge of emerging technologies.
- 🚀 Beginner-friendly content with advanced skill development.
📚 Courses Included:
- AI (Microsoft Certification)
- Introduction to Power BI - Python & SQL
- Human Resource Management
- UI/UX Design
- Finance and Stock Marketing 2.0
- Aptitude Test Preparation
- Stock Market Fundamentals
- Data Science (DS)
- Digital Marketing 3.0
- Foundation to Embedded Systems
- Artificial Intelligence (AI)
- VLSI Design
- Full Stack Web Development with Python Django
- Foundation of AR-VR
- Placemect Training
💡 Unlock your potential and master the latest technologies with this all-in-one skill package!
| Web Development - Front End | |||
| Visual Studio Setup 16:00 | |||
| HTML Fundamentals 58:00 | |||
| CSS Fundamentals ( CSS Syntax and Selectors, Box Model and layout ) 75:00 | |||
| Javascript Basics 74:00 | |||
| Project : Portfolio Part 1 59:00 | |||
| Project : Portfolio Part 2 24:00 | |||
| GitHub Publishing 38:00 | |||
| Power BI: Python & SQL | |||
| Module 1: Data Analyst Overview 4:00 | |||
| Module 2: Power BI Overview 4:00 | |||
| Module 3: Power BI walkthrough 16:00 | |||
| Module 4: Creating Charts - Part 1 29:00 | |||
| Module 5: Creating Charts - Part 2 17:00 | |||
| Module 6: Formatting Charts 23:00 | |||
| Module 7: Filter & Drill 18:00 | |||
| Module 8: Power Query Editor 47:00 | |||
| Module 9: DAX 29:00 | |||
| Module 10: SQL Introduction 18:00 | |||
| Module 11: DDL & DML 19:00 | |||
| Module 12: Constraints 11:00 | |||
| Module 13: SQL Keywords 23:00 | |||
| Module 14: Sub query, Joins, Data and Time manipulation 19:00 | |||
| Module 15: Python introduction 27:00 | |||
| Module 16: NumPy 38:00 | |||
| Module 17: Pandas 61:00 | |||
| Module 18: Creating Github Portfolio 56:00 | |||
| Project : HR Employee Attrition 58:00 | |||
| HR Employee Attiration - Project Files | |||
| Foundation To AR-VR | |||
| Blender - Module 1 = Interface , 3D Fundamentals & ShortCuts 51:00 | |||
| Blender Module 2 - Basics of 3D Modeling 42:00 | |||
| Blender - Short cut Cheat sheet (3 pages) | |||
| Blender Module 3 - Modelling a Japanese House 56:00 | |||
| Project 1: 3D House Model | |||
| 360 VR Rendering Blender 24:00 | |||
| 2D to 3D 51:00 | |||
| Artificial Intelligence & Machine Learning | |||
| Introduction to Artificial Intelligence 26:00 | |||
| Introduction To Machine Learning 59:00 | |||
| History of Artificial Intelligence 20:00 | |||
| Types of Problems in Machine Learning 19:00 | |||
| Linear Regression | |||
| Linear Regression_Demo 42:00 | |||
| logistic Regression 11:00 | |||
| Logistic Regression_Demo 22:00 | |||
| Random Forest Classifier 23:00 | |||
| Random Forest Demo 43:00 | |||
| Naive Bayes Classifiers 30:00 | |||
| Naive Bayes Classifier Demo 17:00 | |||
| K-Nearest Neighbor Classifier 26:00 | |||
| Introduction to Deep Learning 35:00 | |||
| Types of Deep Learning Networks 33:00 | |||
| Long Short Term Memory 23:00 | |||
| LSTM_Demo 47:00 | |||
| Bidirectional Long Short Term Memory 25:00 | |||
| Graph Neural Network 34:00 | |||
| Autoencoders 23:00 | |||
| Autoencoders_demo 49:00 | |||
| Data Science | |||
| Module 1: Intro to Data Science 26:00 | |||
| Module 2: Tools and Technologies 25:00 | |||
| Module 3: Basics of Date 15:00 | |||
| Module 4 - Data Cleaning 24:00 | |||
| Module 5 - Outliners Removing 17:00 | |||
| Module 6 - Encoding Data 17:00 | |||
| Module 7 - EDA 16:00 | |||
| Module 8 - Data Statistics 20:00 | |||
| Module 9 - Data Visualization Techniques 24:00 | |||
| Module 10 - Understanding Correlation 11:00 | |||
| Module 11 - Machine Learning 18:00 | |||
| Module 12 - Supervised Learning 23:00 | |||
| Module 13 - Machine Learning Algorithms 17:00 | |||
| Module 14 - Evaluation of Models using Metrics 19:00 | |||
| Module 15 - Feature Engineering 17:00 | |||
| Module 16 - Feature Selection Techniques 16:00 | |||
| Module 17 - Linear Regression 14:00 | |||
| Module 18 - Logistic Regression 13:00 | |||
| Module 19 - KNN Classifier 12:00 | |||
| Module 20 - SVM 14:00 | |||
| Module 23 - Ensemble Learning and Model Tuning 12:00 | |||
| UI - UX | |||
| Introduction to the Course 3:00 | |||
| Introduction to UI Design 29:00 | |||
| Introduction to UX Design 33:00 | |||
| Introduction to Plugins 12:00 | |||
| Project Workspace and Tools 24:00 | |||
| Overview of Figma's Home page 8:00 | |||
| Download and Login into Figma 6:00 | |||
| Community in Figma 9:00 | |||
| Session 1 - 06 Oct, 2024 41:00 | |||
| Session 2 - 20 Oct, 2024 60:00 | |||
| Session 3 - 26 Oct, 2024 29:00 | |||
| Session 4 - 27 Oct, 2024 36:00 | |||
| Session 5 - 03 Nov, 2024 55:00 | |||
| Session 6 - 10 Nov, 2024 40:00 | |||
| Session 7 - 17 Nov, 2024 36:00 | |||
| Session 8 - 24 Nov, 2024 33:00 | |||
| Session 9 - 1 Dec, 2024 46:00 | |||
| Session 10 - 8 Dec, 2024 45:00 | |||
| Digital Marketing | |||
| Module 1 - Introduction to Digital Marketing 58:00 | |||
| Module 2 - Basic of Email Marketing 59:00 | |||
| Module 3 - Understanding Facebook Business Instagram Business 46:00 | |||
| Module 4 - Understanding Meta Ads Manager 46:00 | |||
| Module 5 - Campaign Creation via Meta 54:00 | |||
| Module 6 - Campaign Creation via Meta Part B 47:00 | |||
| Module 7 - Understanding UTM for Tracking 48:00 | |||
| Module 8 - Exploring Online Reputation Management 51:00 | |||
| Module 9 - Introduction to Search Engine Marketing SEM 49:00 | |||
| Module 10 - Understanding Search Ads 51:00 | |||
| Module 11 - Understanding Match Types for Search Ads 53:00 | |||
| Module 12 - Creating a Google Ad Campaign 74:00 | |||
| Module 13 - Exploring Google My Business 35:00 | |||
| Module 14 - Exploring Search Engine Optimization 54:00 | |||
| Module 15 - Understanding YouTube its Analytics 31:00 | |||
| HR Management | |||
| 1.1 Introduction to HRM 25:00 | |||
| 1.2 Ethics and confidentiality 8:00 | |||
| 1.3 HR Metrics and PI 12:00 | |||
| 1.4 Quiz | |||
| 1.5 Assignment | |||
| 2.1 Recruitment 34:00 | |||
| 2.2 Selection, Interview, JD 22:00 | |||
| 2.3 Employer Branding 10:00 | |||
| 2.4 Social Media and job portals 7:00 | |||
| Job Description | |||
| 3.1 Screening and Shortlisting Theory 15:00 | |||
| 3.2 Screening and shorlisting Practical 5:00 | |||
| 3.3 Interview & Onboarding Form 9:00 | |||
| 4.1 Emloyee records 9:00 | |||
| 4.2 Attendance 13:00 | |||
| 4.3 Payroll and complience 6:00 | |||
| 4.4 Data Security and Comfidentiality 14:00 | |||
| 4.5 Quiz | |||
| 5.1 Company Policies and compliance 30:00 | |||
| Project 1 | |||
| 5.2 Quiz | |||
| Major Project | |||
| 6.1 Compensation Structure 18:00 | |||
| 6.2 Bonus and Incentives 14:00 | |||
| 6.3 Quiz | |||
| 7.1 Employee Tax and compliance 22:00 | |||
| 7.2 Employee Tax Calculation and Compliance Notes | |||
| 7.3 Quiz | |||
| Finance and Stock Marketing | |||
| Support_Resistance_indicators 66:00 | |||
| Multiple candlestick pattern 61:00 | |||
| Single candlestick pattern 63:00 | |||
| Candlestick Formation 64:00 | |||
| Index and Market depth 60:00 | |||
| Shorting and stoploss 64:00 | |||
| Types of orders 62:00 | |||
| need to invest and asset classes 60:00 | |||
| Module 1 - Finance & Tally 23:00 | |||
| Basic of Tally II and Accounting fundamentals 65:00 | |||
| Full Stack Web Development with Python Django | |||
| VLSI | |||
| Embedded Systems | |||
| Cybersecurity | |||
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