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Course Outline
Perkenalan
Pemahaman Big Data
Ikhtisar percikan
Ikhtisar Python
Ikhtisar PySpark
- Mendistribusikan Data Menggunakan Kerangka Kumpulan Data Terdistribusi yang Tangguh
- Mendistribusikan Komputasi Menggunakan Operator Spark API
Menyiapkan Python dengan Spark
Menyiapkan PySpark
Menggunakan Instans EC2 Amazon Web Services (AWS) untuk Spark
Menyiapkan Databricks
Menyiapkan Klaster AWS EMR
Mempelajari Dasar-Dasar Python Programming
- Memulai dengan Python
- Menggunakan Buku Catatan Jupyter
- Menggunakan Variabel dan Tipe Data Sederhana
- Bekerja dengan Daftar
- Menggunakan Pernyataan if
- Menggunakan Input Pengguna
- Bekerja dengan while Loops
- Fungsi Pelaksana
- Bekerja dengan Kelas
- Bekerja dengan File dan Pengecualian
- Bekerja dengan Proyek, Data, dan API
Mempelajari Dasar-dasar Spark DataFrame
- Memulai dengan Spark DataFrames
- Menerapkan Operasi Dasar dengan Spark
- Menggunakan Operasi Groupby dan Agregat
- Bekerja dengan Stempel Waktu dan Tanggal
Mengerjakan Latihan Proyek Spark DataFrame
Memahami Machine Learning dengan MLlib
Bekerja dengan MLlib, Spark, dan Python untuk Machine Learning
Memahami Regresi
- Belajar Teori Regresi Linier
- Menerapkan Kode Evaluasi Regresi
- Mengerjakan Contoh Latihan Regresi Linier
- Belajar Teori Regresi Logistik
- Menerapkan Kode Regresi Logistik
- Mengerjakan Contoh Latihan Regresi Logistik
Pemahaman Random Forest dan Pohon Keputusan
- Teori Metode Pohon Pembelajaran
- Menerapkan Pohon Keputusan dan Random Forest Kode
- Mengerjakan Contoh Random Forest Latihan Klasifikasi
Bekerja dengan Pengelompokan K-means
- Memahami Teori Clustering K-means
- Menerapkan Kode Clustering K-means
- Mengerjakan Contoh Latihan Pengelompokan
Bekerja dengan Sistem Rekomendasi
Menerapkan Pemrosesan Bahasa Alami
- Pemahaman Natural Language Processing (NLP)
- Ikhtisar Alat NLP
- Mengerjakan Contoh Latihan NLP
Streaming dengan Spark di Python
- Ikhtisar Streaming dengan Spark
- Contoh Spark Streaming Latihan
Kata penutup
Requirements
- Keterampilan pemrograman umum
Hadirin
- Pengembang
- Profesional TI
- Ilmuwan Data
21 Hours
Testimonials (6)
I liked that it was practical. Loved to apply the theoretical knowledge with practical examples.
Aurelia-Adriana - Allianz Services Romania
Course - Python and Spark for Big Data (PySpark)
The course was about a series of very complex related topics & Pablo has in-depth expertise of each of them. Sometimes nuances were lost in communication and/or due to time pressures and possibly expectations were not quite met due to this. Also there were some UHG/Azure Databricks setup issues however Pablo / UHG resolved these quickly once they became apparent - this to me showed a high level of understanding and professionalism between UHG & Pablo,
Michael Monks - Tech NorthWest Skillnet
Course - Python and Spark for Big Data (PySpark)
Individual attention.
ARCHANA ANILKUMAR - PPL
Course - Python and Spark for Big Data (PySpark)
Hands on Training..
Abraham Thomas - PPL
Course - Python and Spark for Big Data (PySpark)
The lessons were taught in a Jupyter notebook. The topics were structured with a logical sequence and naturally helped develop the session from the easier parts to the more complex. I'm already an advanced user of Python with background in Machine Learning, so found the course easier to follow than, possibly, some of my classmates that took the training course. I appreciate that some of the most elementary concepts were skipped and that he focused on the most substantial matters.
Angela DeLaMora - ADT, LLC
Course - Python and Spark for Big Data (PySpark)
practice tasks
