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Course Currilcum
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- Working With Real Data 00:00:00
- Discovering the match Between Data Science and Python 00:00:00
- Setting Up Python For Data Science 00:00:00
- Shaping Data 00:00:00
- Visualizing the Data 00:00:00
- EDA 00:00:00
- eda (continued) 00:00:00
- statistics 00:00:00
- eda with statistics 00:00:00
- Linear Regression Introduction 00:00:00
- Linear Regression Assumptions 00:00:00
- Linear regression – practical implementation 00:00:00
- Linear regression – casestudy from scratch 00:00:00
- Linear regression – Quick revision part 1 00:00:00
- Linear regression – quick revision part 2 00:00:00
- Linear regression – interview questions (part 1) 00:00:00
- Linear regression – interview questions (part2) 00:00:00
- Clustering 00:00:00
- clustering – practical implementation 00:00:00
- Moving to Logistic Regression 00:00:00
- Logistic regression practical implementation 00:00:00
- Learning Lazily with Nearest Neighbors 00:00:00
- Usecase 1 implementation from scratch 00:00:00
- Usecase 2 implementation from scratch 00:00:00
- Ten Data Challenges You Should Take 00:00:00
- Making Things as Simple as Na��ve Bayes 00:00:00
- Advanced Regression Quiz 00:05:00
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- Data Science Basics 00:00:00
- Outcomes of Big Data 00:00:00
- Understanding Big Data 00:00:00
- Regression 00:00:00
- Hadoop made simple 00:00:00
- Basic Regression Quiz 00:05:00
- AVODHA Official Hindi YouTube Channel 00:00:00
- Big Data Basic Quiz 00:00:30
- Structured & Unstructured Basics 00:00:00
- Introduction to Mining 00:00:00
- Setting up Data Mining 00:00:00
- Getting into Data Mining 00:00:00
- Octaparsing Live 00:00:00
- Data Mining Quiz -1 00:03:00
- Apache Spark – Session 1 00:00:00
- Apache Spark -Session 2 00:00:00
- Apache Spark Programming Guide 00:00:00
- Apache Kafka Stream processing and DEMO 00:00:00
- Apache Spark Streaming 00:00:00
- Python for Apache Spark – pySpark 00:00:00
- Microsoft Azure- Working with Data Storage 00:00:00
- Microsoft Azure – DataBricks 00:00:00
- Microsoft Azure- Working with Databricks 00:00:00
- Microsoft Azure- Cosmos DB 00:00:00
- Microsoft Azure SQL 00:00:00
- Microsoft Azure Synapse Analytics and PolyBase 00:00:00
- Microsoft Azure Stream Analytics and event hubs 00:00:00
- Microsoft Azure Data Factory Service – ADF 00:00:00
- Microsoft Azure Creating a Virtual Machine 00:00:00
- Microsoft Azure : Securing Data Platforms 00:00:00
- Microsoft Azure – Monitoring and Troubleshooting Data Storage and Processing 00:00:00
- Microsoft Azure : Data Engineer Associate Certification Path- Part 1 00:00:00
- Microsoft Azure : Data Engineer Associate Certification Path- Part 1 00:00:00
- Azure Data Engineer Quiz – Test your Knowledge 00:00:00
- More resources for you 00:00:00
- How To Be A Big Data Engineer 00:00:00
- Quiz – 9 00:10:00
- What are the job opportunities in BigData? 00:00:00
- How to Prepare for a Job Interview 00:00:00
- What is the attitude to work in the Industry 00:00:00
- How to Manage Life and Work 00:00:00
- How to excel in the field 00:00:00
- Finishing HADOOP 00:00:00
- Microsoft Azure Data Engineer Mock Test 00:30:00
- Introduction to AI vs ML vs DS 00:00:00
- Jupyter Notebook and Basic Syntax of Python 00:00:00
- Conditionals and Loops 00:00:00
- Lists and Tuples 00:00:00
- Strings in Python 00:00:00
- Dictionary in Python 00:00:00
- MINI PROJECT: ROCK-PAPER-SCISSORS GAME 00:00:00
- Functions in Python Part-1 00:00:00
- Functions in Python Part-2 00:00:00
- Quiz -10 00:10:00
- MINI PROJECT:SUDOKU SOLVER 00:00:00
- Linear Algebra 00:00:00
- Vector Spaces 00:00:00
- Linear Independence 00:00:00
- Matrix Decomposition 00:00:00
- Machine Learning Basics 00:00:00
- Machine Learning: Foundational Concepts 00:00:00
- Machine Learning – Fundamental Algorithms 00:00:00
- Machine Learning: Hypothesis Space 00:00:00
- Machine Learning – Basic Practice – Part 1 00:00:00
- Machine Learning – Basic Practice – Part 2 00:00:00
- Probability: A Gentle Introduction 00:00:00
- Probability and Distribution – Part 1 00:00:00
- Probability and Distribution – Part 2 00:00:00
- Machine Learning – Problems and Solutions 00:00:00
- Machine Learning – Advanced Practice 00:00:00
- Machine Learning – Unsupervised Learning 00:00:00
- Different Learning Metrics 00:00:00
- Types and Steps of Data Science 00:00:00
- Calculus: Derivatives 00:00:00
- Calculus: Partial Derivatives 00:00:00
- Calculus: Power Series 00:00:00
- Calculus: Fundamental Theorem and Lagrange Multipliers 00:00:00
- Probability and Statistics 00:00:00
- DBMS – Part 1 00:00:00
- DBMS – Part 2 00:00:00
- PostgreSQL 00:00:00
- MySQL 00:00:00