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Overview Business intelligence analysis plays a significant role in determining the success and failure of the business. Hence, skilled analysts are high-value employees in the business sector. If you want to be one of them, start working on your skills. Our exclusive Business Intelligence Analysis Training can help you out with your skill-building In this comprehensive training program, you will get a detailed understanding of business intelligence analysis. The course will educate you on the principles of real-time business analysis, SQL and data management. From the engaging modules, you will learn about statistics and data science. The course will also teach you the strategies of data visualisation and sat warehouse concepts. By the end of the course, you will also grasp the ABCs of Python programming language. This is the perfect skill and career booster. Join now and open new doors or possibilities! Course Preview Learning Outcomes Understand the core principles of real-time business intelligence Grasp a solid understanding of statistics and data science Build your expertise in SQL and database management Develop your skills in data visualisation in business intelligence Introduce yourself to the basics of Python Why Take This Course From John Academy? Affordable, well-structured and high-quality e-learning study materials Meticulously crafted engaging and informative tutorial videos and materials Efficient exam systems for the assessment and instant result Earn UK & internationally recognised accredited qualification Easily access the course content on mobile, tablet, or desktop from anywhere, anytime Excellent career advancement opportunities Get 24/7 student support via email What Skills Will You Learn from This Course? Data management Business intelligence analysis Statistics Who Should Take This Business Intelligence Analysis Training? Whether you're an existing practitioner or an aspiring professional, this course is an ideal training opportunity. It will elevate your expertise and boost your CV with key skills and a recognised qualification attesting to your knowledge. Are There Any Entry Requirements? This Business Intelligence Analysis Training is available to all learners of all academic backgrounds. But learners should be aged 16 or over to undertake the qualification. And a good understanding of the English language, numeracy, and ICT will be helpful. Business Intelligence Analysis Training Certification After completing and passing the Business Intelligence Analysis Training successfully, you will be able to obtain a Recognised Certificate of Achievement. Learners can obtain the certificate in hard copy at £14.99 or PDF format at £11.99. Career Pathâ This exclusive Business Intelligence Analysis Training will equip you with effective skills and abilities and help you explore career paths such as Business Intelligence Analyst Business Executive Entrepreneur Module-1: An Introduction To Business Intelligence An Introduction to Business Intelligence 00:45:00 Module-2: Real-Time Business Intelligence Real-time Business Intelligence 00:34:00 Module-3: Fundamentals Of Statistics And Data Science Fundamentals of Statistics and Data Science 00:49:00 Module-4: Fundamentals Of SQL Fundamentals of SQL 00:39:00 Module-5: Database Management Essentials Database Management Essentials 00:49:00 Module-6: Data Warehouse Concepts Data Warehouse Concepts 00:37:00 Module-7: Data Visualisation In Business Intelligence Data Visualisation in Business Intelligence 00:34:00 Module-8: Basics Of Python Basics of Python 00:26:00 Assignment Assignment - Business Intelligence Analyst 00:00:00 Order Your Certificate and Transcript Order Your Certificates and Transcripts 00:00:00
Overview Are you ready to dive into data analysis and unlock valuable insights that can drive business growth? Introduction to Data Analysis is a comprehensive course designed to provide learners with a solid foundation in the principles and techniques of data analysis. This course will equip you with the essential skills and knowledge to thrive in data analysis. With a comprehensive curriculum spanning 22 modules, you will delve deep into the world of data, from understanding its fundamentals to harnessing it for meaningful insights. Our expertly crafted curriculum covers data collection, process management, statistical tools, control charts, and strategies to deal with variation.Enrol today in this Introduction to Data Analysis course to succeed in all areas of your life. Let your skill become your greatest asset! Key Features of the Course This course equips learners with the essential tools and knowledge to analyse and interpret data accurately. The course is accredited, ensuring its recognition and credibility within the professional community. Learners will have access to 24/7 learning assistance, allowing them to seek guidance and support whenever needed. Who is This course for? This Introduction to Data Analysis course is suitable for students & professionals from various fields, including business, finance, marketing, healthcare, and more. It is also beneficial for individuals looking to enhance their data analysis skills for personal or professional development. What You Will Learn Throughout the course, you will delve into various modules that cover essential concepts and tools for data analysis. Starting with an introduction to process management principles, you will progress through topics such as the voice of the process, customer feedback analysis, and data visualisation using tools like Pareto charts, histograms, and run charts. You will also gain a deep understanding of variation and control charts and learn how to interpret and use them effectively for process improvement. By the end of the course, learners will have a solid understanding of these topics and be able to apply their knowledge to real-world data analysis scenarios. Why Enrol in This Course Data analysis is one of the most sought-after skills in today's job market. According to LinkedIn, data analysis is among the top 10 most in-demand skills for 2023. Data analysis can help you: Improve your decision-making skills and confidence Enhance your problem-solving and critical-thinking abilities Boost your creativity and innovation potential Increase your productivity and efficiency Advance your career and create earning potential Requirements There are no specific prerequisites for this course. However, a basic understanding of mathematics and statistics will be beneficial. Access to a computer with an internet connection is also required to complete the course. Career Path Completing this Introduction to Data Analysis course can lead to various career opportunities in data analysis. Some of the course-related professions in the UK, along with their average salaries, include: Data Analyst (£35,000 - £45,000 per year) Business Analyst (£40,000 - £55,000 per year) Financial Analyst (£40,000 - £60,000 per year) Market Research Analyst (£25,000 - £40,000 per year) Operations Analyst (£35,000 - £50,000 per year) Healthcare Data Analyst (£35,000 - £50,000 per year) Quality Control Analyst (£25,000 - £35,000 per year) Certification Upon successful completion of the course, learners will receive a CPD certificate, validating their achievement and demonstrating their commitment to professional development in the field of data analysis. Course Curriculum 3 sections • 24 lectures • 02:13:00 total length •Module 01: Introduction: 00:02:00 •Module 02: Agenda and Principles of Process Management: 00:06:00 •Module 03: The Voice of the Process: 00:05:00 •Module 04: Working as One Team for Improvement: 00:04:00 •Module 05: Exercise: The Voice of the Customer: 00:03:00 •Module 06: Tools for Data Analysis: 00:07:00 •Module 07: The Pareto Chart: 00:03:00 •Module 08: The Histogram: 00:03:00 •Module 09: The Run Chart: 00:04:00 •Module 10: Exercise: Presenting Performance Data: 00:05:00 •Module 11: Understanding Variation: 00:06:00 •Module 12: The Control Chart: 00:06:00 •Module 13: Control Chart Example: 00:04:00 •Module 14: Control Chart Special Cases: 00:06:00 •Module 15: Interpreting the Control Chart: 00:10:00 •Module 16: Control Chart Exercise: 00:07:00 •Module 17: Strategies to Deal with Variation: 00:06:00 •Module 18: Using Data to Drive Improvement: 00:14:00 •Module 19: A Structure for Performance Measurement: 00:06:00 •Module 20: Data Analysis Exercise: 00:06:00 •Module 21: Course Project: 00:03:00 •Module 22: Test your Understanding: 00:17:00 •Resources - Introduction to Data Analysis: 00:00:00 •Assignment - Introduction to Data Analysis: 00:00:00
Basics of Chatbots with Machine Learning & Python
By Packt
Let's learn the basic concepts for developing chatbots with machine learning models. This compact course will help you learn to use the power of Python to evaluate your chatbot datasets based on conversational notes, online resources, and websites. Garner hands-on practice in text generation with Python for chatbot development.
Overview This comprehensive course on SQL NoSQL Big Data and Hadoop will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This SQL NoSQL Big Data and Hadoop comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? At the end of the course there will be an online written test, which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this SQL NoSQL Big Data and Hadoop. It is available to all students, of all academic backgrounds. Requirements Our SQL NoSQL Big Data and Hadoop is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 14 sections • 130 lectures • 22:34:00 total length •Introduction: 00:07:00 •Building a Data-driven Organization - Introduction: 00:04:00 •Data Engineering: 00:06:00 •Learning Environment & Course Material: 00:04:00 •Movielens Dataset: 00:03:00 •Introduction to Relational Databases: 00:09:00 •SQL: 00:05:00 •Movielens Relational Model: 00:15:00 •Movielens Relational Model: Normalization vs Denormalization: 00:16:00 •MySQL: 00:05:00 •Movielens in MySQL: Database import: 00:06:00 •OLTP in RDBMS: CRUD Applications: 00:17:00 •Indexes: 00:16:00 •Data Warehousing: 00:15:00 •Analytical Processing: 00:17:00 •Transaction Logs: 00:06:00 •Relational Databases - Wrap Up: 00:03:00 •Distributed Databases: 00:07:00 •CAP Theorem: 00:10:00 •BASE: 00:07:00 •Other Classifications: 00:07:00 •Introduction to KV Stores: 00:02:00 •Redis: 00:04:00 •Install Redis: 00:07:00 •Time Complexity of Algorithm: 00:05:00 •Data Structures in Redis : Key & String: 00:20:00 •Data Structures in Redis II : Hash & List: 00:18:00 •Data structures in Redis III : Set & Sorted Set: 00:21:00 •Data structures in Redis IV : Geo & HyperLogLog: 00:11:00 •Data structures in Redis V : Pubsub & Transaction: 00:08:00 •Modelling Movielens in Redis: 00:11:00 •Redis Example in Application: 00:29:00 •KV Stores: Wrap Up: 00:02:00 •Introduction to Document-Oriented Databases: 00:05:00 •MongoDB: 00:04:00 •MongoDB Installation: 00:02:00 •Movielens in MongoDB: 00:13:00 •Movielens in MongoDB: Normalization vs Denormalization: 00:11:00 •Movielens in MongoDB: Implementation: 00:10:00 •CRUD Operations in MongoDB: 00:13:00 •Indexes: 00:16:00 •MongoDB Aggregation Query - MapReduce function: 00:09:00 •MongoDB Aggregation Query - Aggregation Framework: 00:16:00 •Demo: MySQL vs MongoDB. Modeling with Spark: 00:02:00 •Document Stores: Wrap Up: 00:03:00 •Introduction to Search Engine Stores: 00:05:00 •Elasticsearch: 00:09:00 •Basic Terms Concepts and Description: 00:13:00 •Movielens in Elastisearch: 00:12:00 •CRUD in Elasticsearch: 00:15:00 •Search Queries in Elasticsearch: 00:23:00 •Aggregation Queries in Elasticsearch: 00:23:00 •The Elastic Stack (ELK): 00:12:00 •Use case: UFO Sighting in ElasticSearch: 00:29:00 •Search Engines: Wrap Up: 00:04:00 •Introduction to Columnar databases: 00:06:00 •HBase: 00:07:00 •HBase Architecture: 00:09:00 •HBase Installation: 00:09:00 •Apache Zookeeper: 00:06:00 •Movielens Data in HBase: 00:17:00 •Performing CRUD in HBase: 00:24:00 •SQL on HBase - Apache Phoenix: 00:14:00 •SQL on HBase - Apache Phoenix - Movielens: 00:10:00 •Demo : GeoLife GPS Trajectories: 00:02:00 •Wide Column Store: Wrap Up: 00:05:00 •Introduction to Time Series: 00:09:00 •InfluxDB: 00:03:00 •InfluxDB Installation: 00:07:00 •InfluxDB Data Model: 00:07:00 •Data manipulation in InfluxDB: 00:17:00 •TICK Stack I: 00:12:00 •TICK Stack II: 00:23:00 •Time Series Databases: Wrap Up: 00:04:00 •Introduction to Graph Databases: 00:05:00 •Modelling in Graph: 00:14:00 •Modelling Movielens as a Graph: 00:10:00 •Neo4J: 00:04:00 •Neo4J installation: 00:08:00 •Cypher: 00:12:00 •Cypher II: 00:19:00 •Movielens in Neo4J: Data Import: 00:17:00 •Movielens in Neo4J: Spring Application: 00:12:00 •Data Analysis in Graph Databases: 00:05:00 •Examples of Graph Algorithms in Neo4J: 00:18:00 •Graph Databases: Wrap Up: 00:07:00 •Introduction to Big Data With Apache Hadoop: 00:06:00 •Big Data Storage in Hadoop (HDFS): 00:16:00 •Big Data Processing : YARN: 00:11:00 •Installation: 00:13:00 •Data Processing in Hadoop (MapReduce): 00:14:00 •Examples in MapReduce: 00:25:00 •Data Processing in Hadoop (Pig): 00:12:00 •Examples in Pig: 00:21:00 •Data Processing in Hadoop (Spark): 00:23:00 •Examples in Spark: 00:23:00 •Data Analytics with Apache Spark: 00:09:00 •Data Compression: 00:06:00 •Data serialization and storage formats: 00:20:00 •Hadoop: Wrap Up: 00:07:00 •Introduction Big Data SQL Engines: 00:03:00 •Apache Hive: 00:10:00 •Apache Hive : Demonstration: 00:20:00 •MPP SQL-on-Hadoop: Introduction: 00:03:00 •Impala: 00:06:00 •Impala : Demonstration: 00:18:00 •PrestoDB: 00:13:00 •PrestoDB : Demonstration: 00:14:00 •SQL-on-Hadoop: Wrap Up: 00:02:00 •Data Architectures: 00:05:00 •Introduction to Distributed Commit Logs: 00:07:00 •Apache Kafka: 00:03:00 •Confluent Platform Installation: 00:10:00 •Data Modeling in Kafka I: 00:13:00 •Data Modeling in Kafka II: 00:15:00 •Data Generation for Testing: 00:09:00 •Use case: Toll fee Collection: 00:04:00 •Stream processing: 00:11:00 •Stream Processing II with Stream + Connect APIs: 00:19:00 •Example: Kafka Streams: 00:15:00 •KSQL : Streaming Processing in SQL: 00:04:00 •KSQL: Example: 00:14:00 •Demonstration: NYC Taxi and Fares: 00:01:00 •Streaming: Wrap Up: 00:02:00 •Database Polyglot: 00:04:00 •Extending your knowledge: 00:08:00 •Data Visualization: 00:11:00 •Building a Data-driven Organization - Conclusion: 00:07:00 •Conclusion: 00:03:00 •Assignment -SQL NoSQL Big Data and Hadoop: 00:00:00
