Anaconda Ecosystem for Data Scientists - Plan Szkolenia

Anaconda is a free distribution of Python and R programming languages for data science. It provides an easy-to-use platform that simplifies package management and deployment.

This instructor-led, live training (online or onsite) is aimed at data scientists who wish to use the Anaconda ecosystem to capture, manage, and deploy packages and data analysis workflows in a single platform.

By the end of this training, participants will be able to:

Install and configure Anaconda components and libraries.
Understand the core concepts, features, and benefits of Anaconda.
Manage packages, environments, and channels using Anaconda Navigator.
Use Conda, R, and Python packages for data science and machine learning.
Get to know some practical use cases and techniques for managing multiple data environments.

Format of the Course

Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.

Course Customization Options

To request a customized training for this course, please contact us to arrange.

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Opinie uczestników (7)

przykłady i ćwiczenia

Kamil

Szkolenie - Introduction to Data Science and AI using Python

Rzeczowa wiedza poparta doświadczeniem praktycznym. Pierwszy raz brałem udział w szkoleniu 1 osobowym co znaczanie bardziej ułatwiło kontakt i przyswajanie wiedzy, także tutaj też duzy plus.

Mateusz Macalik - LG Energy Solution Wrocław Sp. z o.o.

Szkolenie - Introduction to Data Science

All the examples used and the lecturing style was on point even for a begginer i was able to understand and the training was so patient and always willing to go extra mile when in need of assistance.

Mathipa Chepape - Vodacom

Szkolenie - Big Data Business Intelligence for Telecom and Communication Service Providers

Intensity, Training materials and expertise, Clarity, Excellent communication with Alessandra

Marija Hornis Dmitrovic - Marija Hornis

Szkolenie - Data Science for Big Data Analytics

It is great to have the course custom made to the key areas that I have highlighted in the pre-course questionnaire. This really helps to address the questions that I have with the subject matter and to align with my learning goals.

Winnie Chan - Statistics Canada

Szkolenie - Jupyter for Data Science Teams

Trainer was accommodative. And actually quite encouraging for me to take up the course.

Grace Goh - DBS Bank Ltd

Szkolenie - Python in Data Science

Do aprendizado, conseguir colocar em prática os exercícios propostos.

Samanta - Imdepa Rolamentos

Szkolenie - Qlik Sense for Data Science

Szkolenia Powiązane

Introduction to Data Science and AI using Python

35 godzin

Big Data Business Intelligence for Telecom & Communication Service Providers

35 godzin

Overview

Communications service providers (CSP) are facing pressure to reduce costs and maximize average revenue per user (ARPU), while ensuring an excellent customer experience, but data volumes keep growing. Global mobile data traffic will grow at a compound annual growth rate (CAGR) of 78 percent to 2016, reaching 10.8 exabytes per month.

Meanwhile, CSPs are generating large volumes of data, including call detail records (CDR), network data and customer data. Companies that fully exploit this data gain a competitive edge. According to a recent survey by The Economist Intelligence Unit, companies that use data-directed decision-making enjoy a 5-6% boost in productivity. Yet 53% of companies leverage only half of their valuable data, and one-fourth of respondents noted that vast quantities of useful data go untapped. The data volumes are so high that manual analysis is impossible, and most legacy software systems can’t keep up, resulting in valuable data being discarded or ignored.

With Big Data & Analytics’ high-speed, scalable big data software, CSPs can mine all their data for better decision making in less time. Different Big Data products and techniques provide an end-to-end software platform for collecting, preparing, analyzing and presenting insights from big data. Application areas include network performance monitoring, fraud detection, customer churn detection and credit risk analysis. Big Data & Analytics products scale to handle terabytes of data but implementation of such tools need new kind of cloud based database system like Hadoop or massive scale parallel computing processor ( KPU etc.)

This course work on Big Data BI for Telco covers all the emerging new areas in which CSPs are investing for productivity gain and opening up new business revenue stream. The course will provide a complete 360 degree over view of Big Data BI in Telco so that decision makers and managers can have a very wide and comprehensive overview of possibilities of Big Data BI in Telco for productivity and revenue gain.

Course objectives

Main objective of the course is to introduce new Big Data business intelligence techniques in 4 sectors of Telecom Business (Marketing/Sales, Network Operation, Financial operation and Customer Relation Management). Students will be introduced to following:

Introduction to Big Data-what is 4Vs (volume, velocity, variety and veracity) in Big Data- Generation, extraction and management from Telco perspective
How Big Data analytic differs from legacy data analytic
In-house justification of Big Data -Telco perspective
Introduction to Hadoop Ecosystem- familiarity with all Hadoop tools like Hive, Pig, SPARC –when and how they are used to solve Big Data problem
How Big Data is extracted to analyze for analytics tool-how Business Analysis’s can reduce their pain points of collection and analysis of data through integrated Hadoop dashboard approach
Basic introduction of Insight analytics, visualization analytics and predictive analytics for Telco
Customer Churn analytic and Big Data-how Big Data analytic can reduce customer churn and customer dissatisfaction in Telco-case studies
Network failure and service failure analytics from Network meta-data and IPDR
Financial analysis-fraud, wastage and ROI estimation from sales and operational data
Customer acquisition problem-Target marketing, customer segmentation and cross-sale from sales data
Introduction and summary of all Big Data analytic products and where they fit into Telco analytic space
Conclusion-how to take step-by-step approach to introduce Big Data Business Intelligence in your organization

Target Audience

Network operation, Financial Managers, CRM managers and top IT managers in Telco CIO office.
Business Analysts in Telco
CFO office managers/analysts
Operational managers
QA managers

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