Sessions

Objectifs de cette formation

Programmes de cette formation

- Data Engineering Foundation
1. DATA ENGINEERING INTRODUCTION
2. DATA SOURCES AND DATA IMPORT
3. DATA PROCESSING
4. DATA ENGINEERING PROJECT
- Python Foundation
1. PYTHON BASICS
2. PYTHON CONTROL STATEMENTS
3. PYTHON DATA STRUCTURES
4. PYTHON FUNCTIONS
5. PYTHON NUMPY PACKAGE
6. PYTHON PANDAS PACKAGE
- Data Science Foundation
1. DATA SCIENCE ESSENTIALS
2. DATA ENGINEERING FOUNDATION
3. PYTHON FOR DATA SCIENCE
4. PYTHON FOR DATA SCIENCE
5. R LANGUAGE ESSENTIALS
6. STATISTICS
7. MACHINE LEARNING INTRODUCTION
- Version Control with Git
1. GIT INTRODUCTION
2. GIT REPOSITORY and GitHub
3. COMMITS, PULL, FETCH AND PUSH
4. TAGGING, BRANCHING AND MERGING
5. UNDOING CHANGES
6. GIT WITH GITHUB AND BITBUCKET
- Big Data Foundation
1. BIG DATA INTRODUCTION
2. HDFS AND MAP REDUCE
3. PYSPARK FOUNDATION
4. SPARK SQL and HADOOP HIVE
5. MACHINE LEARNING WITH SPARK ML
6. KAFKA and Spark
- Certified BI Analyst
1. BUSINESS INTELLIGENCE INTRODUCTION
2. BI WITH TABLEAU: INTRODUCTION
3. TABLEAU: CONNECTING TO DATA SOURCE
4. TABLEAU : BUSINESS INSIGHTS
5. DASHBOARDS, STORIES AND PAGES
6. BI WITH POWER-BI
- Database: SQL and MongoDB
1. DATABASE INTRODUCTION
2. SQL BASICS
3. DATA TYPES AND CONSTRAINTS
4. DATABASES AND TABLES (MySQL)
5. SQL JOINS
6. SQL COMMANDS AND CLAUSES
7. DOCUMENT DB/NO-SQL DB
- Data Engineering Associate
1. DATA WAREHOUSE FOUNDATION
2. DOCKER FOUNDATION
3. KUBERNETES CONTAINER ORCHESTRATION
4. DATA ORCHESTRATION WITH APACHE AIRFLOW
5. DATA ENGINEERING PROJECT
- Data Engineering on AWSCloud
1. AWS DATA SERVICES INTRODUCTION
2. DATA INGESTION USING AWS LAMDBA
3. DATA PREPARATION WITH AWS GLUE
4. SPARK APP USING AWS EMR
5. DATA PIPELINE WITH AWS KINESIS
6. DATA WAREHOUSE WITH AWS REDSHIFT
7. DATA ENGINEERING PROJECT
- Data Engineering on Azure Cloud
1. AZURE DATA SERVICES INTRODUCTION
2. STORAGE IN AZURE
3. DATA PIPELINE WITH AZURE SYNAPSE
4. DATA ENGINEERING PROJECT WITH AZURE