Data Science
PGCP-BDA preparation
PG Certificate Programme in Big Data Analytics (PGCP-BDA)
Linux & Cloud, Python & R, Java, Statistics, DBMS, Big Data Technologies, Data Visualization, Practical ML
Curriculum subjects
- Linux Programming and Cloud Computing
- Python and R Programming
- Java Programming
- Advanced Analytics using Statistics
- Data Collection and DBMS (Principles, Tools & Platforms)
- Big Data Technologies
- Data Visualization - Analysis and Reporting
- Practical Machine Learning
- Aptitude & Effective Communication
- Project
CMCE subjects
- • Linux Programming and Cloud Computing & Data Collection and DBMS (Principles, Tools & Platforms)
- • Python & R Programming
- • Java Programming
- • Big Data Technologies
CCEE subjects
- • Advanced Analytics and Statistics
- • Data Visualization - Analysis and Reporting
- • Practical Machine Learning
Notes
Big Data Characteristics, Adoption, Sources and Data Curation
Big Data Technologies
Java Platform, JVM, JDK, Types, Operators and Control Flow
Java Programming
Linux Evolution, GNU, GPL and System Architecture
Linux Programming and Cloud Computing
Python Syntax, Types, Input, Operators and Control Flow
Python and R Programming
File Systems, DBMS Foundations and Codd’s Relational Rules
Data Collection and DBMS
Hadoop Evolution, Ecosystem, Architecture and Operating Modes
Big Data Technologies
Packages, Classpath, Arrays and Program Structure
Java Programming
Installation, Boot Process, systemd and Login
Linux Programming and Cloud Computing
Strings, Tuples, Formatting, Slicing and Sequence Semantics
Python and R Programming
Database Storage, Structured Data and Systematic Data Collection
Data Collection and DBMS
HDFS Architecture, Blocks, NameNodes, DataNodes and Commands
Big Data Technologies
Classes, Objects, Memory, Lifecycle and Wrapper Types
Java Programming
Filesystem Navigation, Files, Links and Archives
Linux Programming and Cloud Computing
Lists, Dictionaries, Sets and Comprehensions
Python and R Programming
SQL DDL, DML, DCL, Constraints, Transactions and Locks
Data Collection and DBMS
HDFS Read and Write Paths, Replication, Rack Awareness and High Availability
Big Data Technologies
Strings, Constructors, Methods, Encapsulation and Static Members
Java Programming
Permissions, Ownership and Access Control Lists
Linux Programming and Cloud Computing
Functions, Arguments, Scope, Lambdas and Functional Tools
Python and R Programming
SQL Filtering, Grouping, Aggregates, Sorting and Conditional Logic
Data Collection and DBMS
Hadoop Cluster Setup, Configuration, Security, Administration and Monitoring
Big Data Technologies
Inheritance, Polymorphism, Abstract Types, Interfaces and Inner Classes
Java Programming
Remote Access, Mounted Storage and the vi Editor
Linux Programming and Cloud Computing
Modules, Packages, Virtual Environments and Serialization
Python and R Programming
Joins, Subqueries, Correlation and Relational Query Design
Data Collection and DBMS
MapReduce Paradigm, Execution Framework and Job Lifecycle
Big Data Technologies
Exceptions, Custom Exceptions and Resource Management
Java Programming
Shell Environment, Expansion, Redirection and Pipelines
Linux Programming and Cloud Computing
Object-Oriented Python: Classes, Inheritance and Polymorphism
Python and R Programming
ER Modeling, Keys, Functional Dependencies and Normalization
Data Collection and DBMS
MapReduce Data Types, Formats, Partitioners, Combiners and Counters
Big Data Technologies
Generics and the Collection Framework
Java Programming
Shell Scripts, Decisions, Loops, Arguments and Functions
Linux Programming and Cloud Computing
Generators, Decorators, Iteration and Regular Expressions
Python and R Programming
Views, Procedures, Functions, Triggers, Cursors and Window Functions
Data Collection and DBMS
Advanced MapReduce, Streaming, Compression, Scheduling and Hadoop ETL
Big Data Technologies
Collection Ordering, Hashing, Iterators and Object Contracts
Java Programming
Processes, Jobs, Signals, Scheduling and Automation
Linux Programming and Cloud Computing
Exceptions, Logging, Files and Reliable Program Structure
Python and R Programming
Data Warehouses, OLTP, OLAP, Dimensional Models and ETL
Data Collection and DBMS
HBase Architecture, Regions, Storage Model and Installation
Big Data Technologies
Enums, Boxing, Annotations and Core Utility Packages
Java Programming
Git, GitHub, Branching and Collaborative Version Control
Linux Programming and Cloud Computing
NumPy Arrays, Vectorization, Broadcasting and Numerical Work
Python and R Programming
NoSQL Models, Storage Architectures and Schema Evolution
Data Collection and DBMS
HBase Shell, Java APIs, CRUD, Scans, Administration and Security
Big Data Technologies
Functional Interfaces, Lambdas and Method References
Java Programming
Cloud Foundations, Characteristics, Vendors and Responsibility
Linux Programming and Cloud Computing
Pandas DataFrames, Wrangling, Cleaning and Aggregation
Python and R Programming
MongoDB Documents, CRUD, Queries and Language Bindings
Data Collection and DBMS
Hive Architecture, Tables, Partitions, Buckets and Storage Formats
Big Data Technologies
Streams, Collectors, Parallel Processing and Date-Time
Java Programming
SaaS, PaaS, IaaS and Cloud Deployment Models
Linux Programming and Cloud Computing
Web Data, Visualization, Images and Audio in Python
Python and R Programming
MongoDB Arrays, Indexes, Ordering and Query Planning
Data Collection and DBMS
Hive Queries, Joins, Views, UDFs, Scripts and Optimization
Big Data Technologies
Threads, Synchronization, Thread Groups and Concurrency
Java Programming
Virtualization, Hypervisors, Provisioning and Migration
Linux Programming and Cloud Computing
Python Database Connectivity and Transactional Data Access
Python and R Programming
MongoDB Aggregation Pipelines and Performance
Data Collection and DBMS
Data Warehouses, Data Lakes, ETL, ELT and Airflow Pipelines
Big Data Technologies
Java I/O, Files, Byte and Character Streams and Serialization
Java Programming
Cloud Operations, Monitoring, Pricing and Application Deployment
Linux Programming and Cloud Computing
R Foundations: Vectors, Matrices, Arrays, Lists and Factors
Python and R Programming
XML Data Models, Querying and Transformation
Data Collection and DBMS
Spark Architecture, RDDs, DataFrames, Spark SQL and Machine Learning
Big Data Technologies
JVM Architecture, Class Metadata and Reflection
Java Programming
AWS EC2, VPC, S3, Lambda and Security Foundations
Linux Programming and Cloud Computing
R Data Frames, Packages, Data Import and Tidy Transformation
Python and R Programming
Cassandra Architecture, Data Modeling, CQL and Operations
Data Collection and DBMS
Spark Structured Streaming, Kafka, Connect and Real-Time Pipelines
Big Data Technologies
JDBC, Transactions, Connection Pooling and DAO Design
Java Programming
Microsoft Azure, DevOps Deployment, Analytics and Cloud Design
Linux Programming and Cloud Computing
R Functions, Statistics, Visualization and R Markdown
Python and R Programming
Enterprise Data Preparation, Cleaning, Lineage and Decisions
Data Collection and DBMS
Practice for PGCP-BDA
Use the learning hub and timed tests with your course target selected in the app.