Data Science Training in Jakarta

Kaggle adalah platform yang bersumber dari banyak orang untuk ilmuwan data. Ini menyediakan platform bagi pengguna untuk menemukan dan menerbitkan kumpulan data berkualitas tinggi, menjelajahi dan membangun model dalam lingkungan ilmu data berbasis web, dan bekerja dengan ilmuwan data lain dan insinyur pembelajaran mesin.Pelatihan langsung yang dipandu instruktur ini (online atau onsite) ditujukan untuk ilmuwan data dan pengembang yang ingin belajar dan membangun karir mereka di Data Science menggunakan Kaggle.Pada akhir pelatihan ini, peserta akan dapat:

Pelajari tentang ilmu data dan pembelajaran mesin. Jelajahi analitik data. Pelajari tentang Kaggle dan cara kerjanya.

Format Kursus

Kuliah dan diskusi interaktif. Banyak latihan dan latihan. Implementasi langsung di lingkungan lab langsung.

Opsi Penyesuaian Kursus

Untuk meminta pelatihan khusus untuk kursus ini, silakan hubungi kami untuk mengaturnya.

In the first part of this training, we cover the fundamentals of MATLAB and its function as both a language and a platform.  Included in this discussion is an introduction to MATLAB syntax, arrays and matrices, data visualization, script development, and object-oriented principles. In the second part, we demonstrate how to use MATLAB for data mining, machine learning and predictive analytics. To provide participants with a clear and practical perspective of MATLAB's approach and power, we draw comparisons between using MATLAB and using other tools such as spreadsheets, C, C++, and Visual Basic. In the third part of the training, participants learn how to streamline their work by automating their data processing and report generation. Throughout the course, participants will put into practice the ideas learned through hands-on exercises in a lab environment. By the end of the training, participants will have a thorough grasp of MATLAB's capabilities and will be able to employ it for solving real-world data science problems as well as for streamlining their work through automation. Assessments will be conducted throughout the course to gauge progress. Format of the Course

• Course includes theoretical and practical exercises, including case discussions, sample code inspection, and hands-on implementation.

Note

• Practice sessions will be based on pre-arranged sample data report templates. If you have specific requirements, please contact us to arrange.

The training course will help the participants prepare for Web Application Development using Python Programming with Data Analytics. Such data visualization is a great tool for Top Management in decision making.

Participants who complete this training will gain a practical, real-world understanding of Data Science and its related technologies, methodologies and tools. Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class. The course starts with an introduction to elemental concepts of Data Science, then progresses into the tools and methodologies used in Data Science. Audience

• Developers
• Technical analysts
• IT consultants

Format of the Course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

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

Python is a programming language that has gained huge popularity in the financial industry. Adopted by the largest investment banks and hedge funds, it is being used to build a wide range of financial applications ranging from core trading programs to risk management systems. In this instructor-led, live training, participants will learn how to use Python to develop practical applications for solving a number of specific finance related problems. By the end of this training, participants will be able to:

• Understand the fundamentals of the Python programming language
• Download, install and maintain the best development tools for creating financial applications in Python
• Select and utilize the most suitable Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
• Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
• Troubleshoot, integrate, deploy, and optimize a Python application

Audience

• Developers
• Analysts
• Quants

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

• This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.

This is a 5 day introduction to Data Science and Artificial Intelligence (AI). The course is delivered with examples and exercises using Python 

Data science is the application of statistical analysis, machine learning, data visualization and programming for the purpose of understanding and interpreting real-world data. F# is a well suited programming language for data science as it combines efficient execution, REPL-scripting, powerful libraries and scalable data integration. In this instructor-led, live training, participants will learn how to use F# to solve a series of real-world data science problems. By the end of this training, participants will be able to:

• Use F#'s integrated data science packages
• Use F# to interoperate with other languages and platforms, including Excel, R, Matlab, and Python
• Use the Deedle package to solve time series problems
• Carry out advanced analysis with minimal lines of production-quality code
• Understand how functional programming is a natural fit for scientific and big data computations
• Access and visualize data with F#
• Apply F# for machine learning

Explore solutions for problems in domains such as business intelligence and social gaming Audience

• Developers
• Data scientists

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

This instructor-led, live training (online or onsite) is aimed at professionals who wish to start a career in Data Science. By the end of this training, participants will be able to:

• Install and configure Python and MySql.
• Understand what Data Science is and how it can add value to virtually any business. 
• Learn the fundamentals of coding in Python
• Learn supervised and unsupervised Machine Learning techniques, and how to implement them and interpret the results.  

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.

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

The explosion of information and data in today’s world is un-paralleled, our ability to innovate and push the boundaries of the possible is growing faster than it ever has. The role of Data Scientist is one of the highest in-demand skills across industry today. We offer much more than learning through theory; we deliver practical, marketable skills that bridge the gap between the world of academia and the demands of industry. This 7 week curriculum  can be tailored to your specific Industry requirements, please contact us for further information or visit the Nobleprog Institute website  Audience: This programme is aimed post level graduates as well as anyone with the required pre-requisite skills which will be determined by an assessment and interview.  Delivery: Delivery of the course will be a mixture of Instructor Led Classroom and Instructor Led Online; typically the 1st week will be 'classroom led', weeks 2 - 6 'virtual classroom' and week 7  back to 'classroom led'.     

Big data is data sets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy.

This course is meant for Marketing Sales Professionals who are intending to get deeper into application of data science in Marketing/ Sales. The course provides
detailed coverage of different data science techniques used for “upsale”, “cross-sale”, market segmentation, branding and CLV. Difference of Marketing and Sales - How is that sales and marketing are different? In very simplewords, sales can be termed as a process which focuses or targets on individuals or small groups. Marketing on the other hand targets a larger group or the general public. Marketing includes research (identifying needs of the customer), development of products (producing innovative products) and promoting the product (through advertisements) and create awareness about the product among the consumers. As such marketing means generating leads or prospects. Once the product is out in the market, it is the task of the sales person to persuade the customer to buy the product. Sales means converting the leads or prospects into purchases and orders, while marketing is aimed at longer terms, sales pertain to shorter goals.

Jupyter adalah IDE interaktif dan lingkungan komputasi sumber terbuka berbasis web. Pelatihan langsung yang dipimpin instruktur (online atau di lokasi) ini memperkenalkan gagasan pengembangan kolaboratif dalam ilmu data dan mendemonstrasikan cara menggunakan Jupyter untuk melacak dan berpartisipasi sebagai tim dalam "siklus hidup ide komputasi". Ini memandu peserta melalui pembuatan contoh proyek ilmu data berdasarkan ekosistem Jupyter. Pada akhir pelatihan ini, peserta akan mampu:

• Instal dan konfigurasikan Jupyter, termasuk pembuatan dan integrasi repositori tim di Git.
• Gunakan fitur Jupyter seperti ekstensi, widget interaktif, mode multipengguna, dan lainnya untuk mengaktifkan kolaborasi proyek.
• Buat, bagikan, dan atur Jupyter Notebooks dengan anggota tim.
• Pilih dari Scala, Python, R, untuk menulis dan mengeksekusi kode terhadap sistem data besar seperti Apache Spark, semuanya melalui antarmuka Jupyter.

Format Kursus

• Ceramah dan diskusi interaktif.
• Banyak latihan dan latihan.
• Implementasi langsung di lingkungan laboratorium langsung.

Opsi Kustomisasi Kursus

• Notebook Jupyter mendukung lebih dari 40 bahasa termasuk R, Python, Scala, Julia, dll. Untuk menyesuaikan kursus ini dengan bahasa pilihan Anda, silakan hubungi kami untuk mengaturnya.

KNIME Analytics Platform is a leading open source option for data-driven innovation, helping you discover the potential hidden in your data, mine for fresh insights, or predict new futures. With more than 1000 modules, hundreds of ready-to-run examples, a comprehensive range of integrated tools, and the widest choice of advanced algorithms available, KNIME Analytics Platform is the perfect toolbox for any data scientist and business analyst. This course for KNIME Analytics Platform is an ideal opportunity for beginners, advanced users and KNIME experts to be introduced to KNIME, to learn how to use it more effectively, and how to create clear, comprehensive reports based on KNIME workflows This instructor-led, live training (online or onsite) is aimed at data professionals who wish to use KNIME to solve complex business needs. It is targeted for the audience that doesn't know programming and intends to use cutting edge tools to implement analytics scenarios By the end of this training, participants will be able to:

• Install and configure KNIME.
• Build Data Science scenarios
• Train, test and validate models
• Implement end to end value chain of data science models

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 or to know more on this program, please contact us to arrange.

KNIME Server is the enterprise software for team-based collaboration, automation, management, and deployment of data science workflows as analytical applications and services. By the end of this training, participants will be able to:

• Schedule analytics workflows to run automatically and give yourself more time to focus on data science.
• Control workflows to automate model management
• Scale and pin workflow execution with well provisioned, high performance server architecture which is configured to your specifications.
• Design, edit, and execute workflows on KNIME Server using the remote workflow editor and take advantage of well provisioned hardware in a secure environment.

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 or to know more on this program, please contact us to arrange.

Presto is a distributed query engine for big data analytics. Using Presto, users can natively query data, access data from multiple systems, and more. This instructor-led, live training (online or onsite) is aimed at data scientists who wish to query big data sources with Presto. By the end of this training, participants will be able to:

• Employ Presto key concepts to optimize modern big data systems.
• Use Presto to run exabyte scale warehouses.
• Clone data to a proprietary data storage system.
• Work with existing BI tools such as R and Tableau.

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.

Qlik Sense is a cloud-based data analytical software for analyzing and displaying data. With Qlik Sense, users will be able to gain impactful insights by connecting to different data sources and creating advanced visualizations. This instructor-led, live training (online or onsite) is aimed at data analysts and web developers who wish to develop associative models in Qlik Sense. By the end of this training, participants will be able to:

• Apply Qlik Sense in data science.
• Use and navigate the Qlik Sense interface.
• Build a data literate workforce with AI interaction.
• Create a data-driven enterprise with Qlik Sense.

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.

Practical Quantum Computing: Live Online Launch your high-tech career This is a 10 hour instructor-led, live online training course. After your immersive training, you will be ready to start work as an entry level quantum computing developer. By the end of this training, participants will be able to:

• Run and test your quantum programs with the integrated IBM Q
• Use Qiskit to create, compile, and execute quantum computing programs
• Working with practical and advanced quantum algorithms such as QAOA 
• Recast real-world problems into an appropriate quantum computing language

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.

This classroom based training session will contain presentations and Q&A sessions

SMACK is a collection of data platform softwares, namely Apache Spark, Apache Mesos, Apache Akka, Apache Cassandra, and Apache Kafka. Using the SMACK stack, users can create and scale data processing platforms. This instructor-led, live training (online or onsite) is aimed at data scientists who wish to use the SMACK stack to build data processing platforms for big data solutions. By the end of this training, participants will be able to:

• Implement a data pipeline architecture for processing big data.
• Develop a cluster infrastructure with Apache Mesos and Docker.
• Analyze data with Spark and Scala.
• Manage unstructured data with Apache Cassandra.

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.

Anaconda adalah distribusi bebas dari bahasa pemrograman Python dan R untuk ilmu data. Ini menyediakan platform yang mudah digunakan yang memudahkan pengelolaan paket dan pemasangan. Pelatihan ini didorong oleh instruktur, secara langsung (online atau on-site) ditujukan untuk ilmuwan data yang ingin menggunakan ekosistem Anaconda untuk menangkap, mengelola, dan mengimplementasikan paket dan aliran kerja analisis data dalam satu platform. Pada akhir latihan ini, peserta akan dapat:

Menginstal dan mengkonfigurasi Anaconda komponen dan perpustakaan. Memahami konsep inti, fitur, dan manfaat dari Anaconda. Mengelola paket, lingkungan, dan saluran menggunakan Anaconda Navigator. Gunakan paket Conda, R, dan Python untuk ilmu data dan pembelajaran mesin. Ketahui beberapa kasus dan teknik penggunaan praktis untuk mengelola lingkungan data yang berbilang.

Format Kursus

Konferensi dan diskusi interaktif. Banyak latihan dan praktek. Pelaksanaan tangan di lingkungan live-lab.

Opsi Customization Kursus

Untuk meminta pelatihan tersuai untuk kursus ini, silakan hubungi kami untuk mengatur.

RAPIDS adalah suite perpustakaan perangkat lunak sumber terbuka yang dibangun untuk mempercepat GPU-driven data sains dan pipa analisis. Ini didasarkan pada Python dan mencakup DataFrame API yang berintegrasi dengan berbagai algoritma pembelajaran mesin. Pelatihan ini didorong oleh instruktur, secara langsung (online atau on-site) ditujukan untuk ilmuwan data dan pengembang yang ingin menggunakan RAPIDS untuk membangun GPU-pipa data dipercepat, aliran kerja, dan visualisasi, menerapkan algoritma pembelajaran mesin, seperti XGBoost, cuML, dll. Pada akhir latihan ini, peserta akan dapat:

Menetapkan lingkungan pengembangan yang diperlukan untuk membangun model data dengan NVIDIA RAPIDS. Memahami ciri-ciri, komponen, dan manfaat dari RAPIDS. Leverage GPUs untuk mempercepat end-to-end data dan pipa analisis. Mengimplementasikan persiapan data yang dipercepat GPU dan ETL dengan cuDF dan Apache Arrow. Pelajari cara melakukan tugas pembelajaran mesin dengan algoritma XGBoost dan cuML. Membangun visualisasi data dan melakukan analisis grafis dengan cuXfilter dan cuGraph.

Format Kursus

Konferensi dan diskusi interaktif. Banyak latihan dan praktek. Pelaksanaan tangan di lingkungan live-lab.

Opsi Customization Kursus

Untuk meminta pelatihan tersuai untuk kursus ini, silakan hubungi kami untuk mengatur.

Modin adalah sistem kerangka data paralel yang dirancang untuk mempercepat Pandas aliran kerja. Ini dapat digunakan untuk menangani set data besar, memanfaatkan Ray atau Dask sebagai rangka kerja backend untuk pengkomputeran teragih dalam Python. Pelatihan ini didorong oleh instruktur, secara langsung (online atau on-site) ditujukan untuk ilmuwan data dan pengembang yang ingin menggunakan Modin untuk membangun dan menerapkan komputasi paralel dengan Pandas untuk analisis data yang lebih cepat. Pada akhir latihan ini, peserta akan dapat:

Menetapkan lingkungan yang diperlukan untuk memulai pengembangan Pandas aliran kerja pada skala dengan Modin. Memahami ciri-ciri, arsitektur, dan manfaat dari Modin. Ketahuilah perbedaan antara dua, satu, dan Ray. Untuk melakukan operasi Pandas lebih cepat dengan Modin. Mengimplementasikan seluruh Pandas API dan fungsi.

Format Kursus

Konferensi dan diskusi interaktif. Banyak latihan dan praktek. Pelaksanaan tangan di lingkungan live-lab.

Opsi Customization Kursus

Untuk meminta pelatihan tersuai untuk kursus ini, silakan hubungi kami untuk mengatur.