Data Engineering Foundations Part 2: Building Data Pipelines with Kafka and Nifi

Colleagues, the “Data Engineering Foundations Part 2: Building Data Pipelines with Kafka and NiFi” program introduces you to creating data pipelines at scale with Kafka and NiFi. You learn to work with the Kafka message broker and discover how to establish NiFi dataflow. You also learn about data movement and storage. All software used in videos is open source and freely available for your use and experimentation on the included virtual machine. Learn Kafka topics, brokers, and partitions, implement basic Kafka usage modes, Kafka producers and consumers with Python, KafkaEsque graphical user interface, core concepts of NiFi, NiFi flow and web UI components, direct data movement with HDFS, HBase with Python Happybase and Sqoop for database movement. Skill-based lessons address: 1) Working with the Kafka Message Broker - Kafka message broker concept and describes the producer-consumer model that enables input data to be reliably decoupled from output requests. Kafka producers and consumers are developed using Python, and internal broker operations are displayed using the Kafkaesque graphical user interface, 2) Working with NiFi Dataflow - Lesson 8 begins with a description of NiFi flow-based programming and then provides several examples that include writing pipeline data to the local file system, then to the Hadoop Distributed File System, and finally to Hadoop Hive tables. The entire flow process is constructed using the NiFi web Graphical User Interface. The creation of portable flow templates for all examples is also presented, 3) Big Data Movement and Storage - moving data to and from the Hadoop Distributed File System. Hands-on examples include direct web downloads and using Python Pydoop to move data. Basic data movement between Apache HBase, Hive, and Spark using Python Happybase and Hive-SQL. Finally, movement of relational data to and from the Hadoop Distributed File System is demonstrated using Apache Sqoop.

Enroll today (teams & executives are welcome): https://tinyurl.com/bdpz4vf 

Download your free Data Science  - Career Transformation Guide.

Explore our Data-Driven Organizations Audible and Kindle book series on Amazon:

1 - Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age (Audible) (Kindle) 

Much career success, Lawrence E. Wilson - AI Academy (share with your team)

Implementing Data Science Methodology - From Data Wrangling to Data Viz and Everything in Between (Audible & Kindle Book)

Colleagues, the book entitled “Implementing Data Science Methodology … From Data Wrangling to Data Viz and Everything in Between” will enable you to lead data science initiatives within your organization. They allow organizations to make informed decisions based on data, which can lead to better results and increased competitiveness. Data-driven methodologies also help organizations to identify areas for improvement and to make more accurate predictions about future outcomes and improve the accuracy of decision-making. By analyzing large amounts of data, organizations can identify patterns and trends that would not be apparent otherwise. This allows them to make more informed decisions, reducing the risk of making decisions based on inaccurate or incomplete information. The implementation of data-driven methodologies is critical for organizations looking to remain competitive in today’s data-driven world. By leveraging data to make informed decisions, organizations can improve their performance, reduce risks, and provide better experiences for their customers. It is important for organizations to invest in the resources and processes needed to implement these methodologies effectively, and to stay up-to-date with the latest trends and technologies in data science. Key topics addressed include: 1) Data-Driven Methodologies, 2) The Role of the Data Scientist, 3) Stakeholders and Buy-in, 4) Key Concepts of Data-Driven Methodology, 5) Data-Driven Lifecycle, 6) Data-driven Roadmapping, 6) Planning and Implementing a Data-Driven Strategy, 7) Data-Driven Predictive Modeling, 8) Business Transformation, and 9) Examples of Data-Driven Organizations.

Access on Amazon today!  

(Audible) Listen

(Kindle) Read

And download your free Data Science - Career Transformation Guide.

Regards, Genesys Digital (Amazon Author Page) https://tinyurl.com/hh7bf4m9 

Share Data Through the Art of Visualization (Google)

Colleagues, Share Data Through the Art of Visualization is the sixth course in the Google Data Analytics Certificate. You’ll learn how to visualize and present your data findings as you complete the data analysis process. This course will show you how data visualizations, such as visual dashboards, can help bring your data to life. You’ll also explore Tableau, a data visualization platform that will help you create effective visualizations for your presentations. Current Google Data Analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary. By the end of this course you will - Understand the importance of data visualization. - Learn how to form a compelling narrative through data stories. - Gain an understanding of how to use Tableau to create dashboards and dashboard filters. - Discover how to use Tableau to create effective visualizations. - Explore the principles and practices involved with effective presentations. - Learn how to consider potential limitations associated with the data in your presentations. - Understand how to apply best practices to a Q&A with your audience.

Enroll today (teams & executives are welcome): imp.i384100.net/vN7W4A 

Download your free Data Science  - Career Transformation Guide.

Explore our Data-Driven Organizations Audible and Kindle book series on Amazon:

1 - Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age (Audible) (Kindle) 

Much career success, Lawrence E. Wilson - AI Academy (share with your team)

Python: Data Science and Machine Learning Recipes

Dev colleagues, the Python: Data Science and Machine Learning Recipes training offers a hands-on approach to building your Python skills through a series of practical projects from scratch. Hone your expertise in areas such as data analysis, machine learning, web scraping, and more. Skill-based lessons include: 1)  Manipulate and Visualize Data in Jupyter - Get started with Jupyter Notebooks, Load data into Jupyter, Manipulate data with Pandas, Visualize data; 2) Perform Sentiment Analysis - Sentiment Analysis tools in Python, Learn the basics of NLTK, Incorporate Sentiment Analysis into an application, Analyze with real-world data; 3) Work with Image Recognition - Learn about image recognition tools in Python, Learn the basics of OpenCV, Incorporate image recognition into an application; 4) Scrape Data from the Internet - Learn about web-scraping tools in Python and the basics of the Beautiful Soup Library, Format and use scraped data, and Modify web-scraping logic for other websites. 

Enroll today (teams & executives are welcome): https://tinyurl.com/2brapsfz 

Download your free Data Science  - Career Transformation Guide.

Explore our Data-Driven Organizations Audible and Kindle book series on Amazon:

1 - Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age (Audible) (Kindle) 

Much career success, Lawrence E. Wilson - AI Academy (share with your team)

Microsoft Power BI Data Analyst - Certification Training (PL-300)

Colleagues, when you complete the Microsoft Power BI Data Analyst  program you will receive a 50% discount voucher to take the PL-300 Certification Exam. Business Intelligence analysts are highly sought after as more organizations rely on data-driven decision-making. Microsoft Power BI is the leading data analytics, business intelligence, and reporting tool in the field, used by 97% of Fortune 500 companies to make decisions based on data-driven insights and analytics. Prepare for a new career in this high-growth field with professional training from Microsoft - an industry-recognized leader in data analytics and business intelligence. Through a mix of videos, assessments, and hands-on activities, you will engage with the key concepts of Power BI, transforming data into meaningful insights and creating compelling reports and dashboards. You will learn to prepare data in Excel for analysis in Power BI, form data models using the Star schema, perform calculations in DAX, and more.\n\nIn your final project, you will showcase your new Power BI and data analysis skills using a real-world scenario. When you complete this Professional Certificate, you’ll have tangible examples to talk about in your job interviews and you’ll also be prepared to take the industry-recognized PL-300: Microsoft Power BI Data Analyst certification exam. Microsoft was named a Leader in the 2023 Gartner® Magic Quadrant™ for Analytics and BI Platforms (April 2023).

Enroll today (teams & executives are welcome): imp.i384100.net/5gVKk2  

Download your free Data Science  - Career Transformation Guide.

Explore our Data-Driven Organizations Audible and Kindle book series on Amazon:

1 - Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age (Audible) (Kindle) 

Much career success, Lawrence E. Wilson - AI Academy (share with your team)

AI Software Engineer: ChatGPT, Bard and Beyond (audio & ebook)

Colleagues, the purpose of the “AI Software Engineer: ChatGPT, Bard and Beyond” (Interview Prodigy series) help software engineers and developers capture their ideal job offer and manage their medium-to-long-term career growth in the global artificial intelligence arena. We will focus on artificial intelligence software engineers and developers in this series. Artificial intelligence has proven to be a revolutionary part of the digital era. As a result, top tech giants like Amazon, Google, Apple, Facebook, Microsoft, and International Business Machines Corporation have been investing significantly in the research and development of artificial intelligence. As a result, these companies are contributing well to making A.I. more accessible for businesses. In addition, different companies have adopted A.I. technology for improved customer experience. For example, in March 2020, McDonald's invested $300 million to acquire an A.I. startup in Tel Aviv to provide a personalized experience for its customers using artificial intelligence. This was its most significant tech investment.

AI Engineers have many opportunities, which will only grow with time. After reading this book, I hope you can identify your ideal job offer and manage your short- and long-term career growth plan, especially in artificial intelligence. The world of artificial intelligence is vast. As I stated earlier in this book, it has a current market size of $136.55 billion based on a 2022 report by CAGR, and it will likely reach a growth rate of 37.3% from 2023 to 2030. You can study artificial intelligence from three aspects. First, the narrow artificial intelligence: this is where you learn about strong AI, artificial general intelligence, and narrow artificial intelligence, also known as weak AI. As I mentioned earlier in this book, the tech we use daily is known as narrow artificial intelligence mainly because it focuses on one narrow task. An example is a chess computer, Siri, or Alexa. Artificial narrow intelligence generally operates within a limited predetermined range. Then there is machine learning, an application that allows systems and computers to learn and improve without being programmed. This idea aims to enable systems to learn and adapt automatically without human involvement or support. Deep learning enables inventors to enhance technology such as self-driving vehicles, speech recognition, and facial identification.

Order today: 

(Audible) https://tinyurl.com/mae9ku3b

 (Kindle) https://tinyurl.com/27jux34w 

 “Interview Prodigy” audio & ebook series on Amazon for your reading-listening pleasure (https://tinyurl.com/57ehhjb2). 

1 - AI Software Engineer: ChatGPT, Bard & Beyond (Audible) (Kindle) 

2 - JavaScript Full Stack Developer: Capture the Job Offer and Advance Your Career  (Audible) (Kindle)

3 -  The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age  (Audible) (Kindle)

Regards, Genesys Digital (Amazon Author Page) https://tinyurl.com/hh7bf4m9

Deep Learning: From Perceptron to Large Language Models

Colleagues, in the Deep Learning: From Perceptron to Large Language Models program you will understand the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, recurrent layers, how to build advanced architectures, including the Transformer, TensorFlow and encoders. He describes how these concepts are used to build modern networks for computer vision and Natural Language Processing (NLP), including large language models and multimodal networks. The code repository is located on github.com/NVDLI/LDL. Learn how to Apply core concepts of perceptrons, gradient-based learning, sigmoid neurons, and backpropagation, Utilize DL frameworks to make it easier to develop more complicated and useful neural networks, Utilize convolutional neural networks (CNNs) to perform image classification and analysis, Apply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequences, Build a natural language translation application using sequence-to-sequence networks based on the transformer architecture, Use the transformer architecture for other natural language processing (NLP) tasks, and how to engineer prompts for large language models (LLM), and Combine image and text data and build multimodal networks, including an image captioning application. Skill-based lessons cover: 1) Deep Learning Introduction, 2) Neural Network Fundamentals I & II, 3) Convolutional Neural Networks (CNN) and Image Classification, 4) Recurrent Neural Networks (RNN) and Time Series Prediction, 5) Neural Language Models and Word Embeddings, 6) Encoder-Decoder Networks, Attention, Transformers, and Neural Machine Translation, 7) Large Language Models, 8) Multi-modal Networks and Image Captioning, 9) Multi-task Learning and Computer Vision Beyond Classification, and 10) Applying Deep Learning.

Enroll today (teams & execs welcome): https://tinyurl.com/47bs2k86 

Download your free AI-ML-DL - Career Transformation Guide.

For your listening-reading pleasure:

1 - “AI Software Engineer: ChatGPT, Bard & Beyond” (Audible) or (Kindle)  

2 - “ChatGPT - The Era of Generative Conversational AI Has Begun” (Audible) or (Kindle) 

3 - “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) or (Kindle) 

Much career success, Lawrence E. Wilson - AI Academy (share with your team)