569 Machine Learning (ML) courses

Are you looking to enhance your Python- Beginner to Advance skills? If yes, then you have come to the right place. Our comprehensive course on Python- Beginner to Advance will assist you in producing the best possible outcome by mastering the Python- Beginner to Advance skills. The Python- Beginner to Advance course is for those who want to be successful. In the Python- Beginner to Advance course, you will learn the essential knowledge needed to become well versed in Python- Beginner to Advance. Our course starts with the basics of Python- Beginner to Advance and gradually progresses towards advanced topics. Therefore, each lesson of this Python- Beginner to Advance course is intuitive and easy to understand. Why would you choose the Python- Beginner to Advance course from Compliance Central: Lifetime access to Python- Beginner to Advance course materials Full tutor support is available from Monday to Friday with the Python- Beginner to Advance course Learn Python- Beginner to Advance skills at your own pace from the comfort of your home Gain a complete understanding of Python- Beginner to Advance course Accessible, informative Python- Beginner to Advance learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Python- Beginner to Advance course Study Python- Beginner to Advance in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Python- Beginner to Advance course Curriculum Breakdown of the Python- Beginner to Advance Course Introduction Curriculum Overview What's New command line basics python installation Pycham-ce ide installation Setting up environment Running python code git and github overview Python Data Types Python Arithmetic Operators Numbers Variable Assignments Strings Introduction Indexing and Slicing with Strings String Properties and Methods CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Python- Beginner to Advance course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Python- Beginner to Advance. It is also great for professionals who are already working in Python- Beginner to Advance and want to get promoted at work. Requirements To enrol in this Python- Beginner to Advance course, all you need is a basic understanding of the English Language and an internet connection. Career path The Python- Beginner to Advance course will enhance your knowledge and improve your confidence in exploring opportunities in various sectors. Python Developer: £35,000 to £70,000 per year Data Analyst: £25,000 to £55,000 per year Machine Learning Engineer: £45,000 to £85,000 per year Software Engineer: £40,000 to £75,000 per year Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99 each

About Course Data Science and Data Analytics with Python: A Comprehensive Course for Beginners Unlock the power of data and gain insights that drive informed decisions with this comprehensive course on data science and data analytics with Python. This course is designed for beginners of all skill levels, with no prior programming experience required. You will learn the essential skills to embark on your data-driven journey, including: Data manipulation with NumPy and Pandas Data visualization with Matplotlib and Seaborn Statistical analysis with Python Machine learning and artificial intelligence You will also gain hands-on experience with real-world data projects, allowing you to apply your newfound knowledge to solve real-world problems. By the end of this course, you will be able to: Understand the fundamentals of data science and data analytics Apply Python to manipulate, visualize, and analyze data Use Python to build machine learning and artificial intelligence models Solve real-world data problems This course is the perfect launchpad for your data science journey. Whether you are looking to pivot your career, enhance your skill set, or simply quench your curiosity, this course will give you the foundation you need to succeed. Enroll today and start exploring the fascinating world of data science together! What Will You Learn? Understand the fundamentals of data science and data analytics Apply Python to manipulate, visualize, and analyze data Use Python to build machine learning and artificial intelligence models Solve real-world data problems Course Content Introduction to Python Data Science Introduction to Python Data Science Environment Setup Data Cleaning Packages Working with the Numpy package Working with Pandas Data science package Data Visualization Packages Working with Matplotlib Data Science package (Part - 1) Working with Matplotlib Data Science (Part - 2) A course by Uditha Bandara Microsoft Most Valuable Professional (MVP) RequirementsBeginners level knowledge for working with Data .Programming knowledge not required. Audience Beginners with no prior programming experience Anyone interested in learning data science and data analytics Audience Beginners with no prior programming experience Anyone interested in learning data science and data analytics

Duration 1 Days 6 CPD hours This course is intended for This course is designed for data scientists with experience of Python who need to learn how to apply their data science and machine learning skills on Azure Databricks. Overview After completing this course, you will be able to: Provision an Azure Databricks workspace and cluster Use Azure Databricks to train a machine learning model Use MLflow to track experiments and manage machine learning models Integrate Azure Databricks with Azure Machine Learning Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this course, students will learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning. Introduction to Azure Databricks Getting Started with Azure Databricks Working with Data in Azure Databricks Training and Evaluating Machine Learning Models Preparing Data for Machine Learning Training a Machine Learning Model Managing Experiments and Models Using MLflow to Track Experiments Managing Models Managing Experiments and Models Using MLflow to Track Experiments Managing Models Integrating Azure Databricks and Azure Machine Learning Tracking Experiments with Azure Machine Learning Deploying Models

Duration 1 Days 6 CPD hours This course is intended for This class is intended for the following: Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform. Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports. Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists. Overview This course teaches students the following skills:Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.Employ BigQuery and Cloud Datalab to carry out interactive data analysis.Train and use a neural network using TensorFlow.Employ ML APIs.Choose between different data processing products on the Google Cloud Platform. This course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. Introducing Google Cloud Platform Google Platform Fundamentals Overview. Google Cloud Platform Big Data Products. Compute and Storage Fundamentals CPUs on demand (Compute Engine). A global filesystem (Cloud Storage). CloudShell. Lab: Set up a Ingest-Transform-Publish data processing pipeline. Data Analytics on the Cloud Stepping-stones to the cloud. Cloud SQL: your SQL database on the cloud. Lab: Importing data into CloudSQL and running queries. Spark on Dataproc. Lab: Machine Learning Recommendations with Spark on Dataproc. Scaling Data Analysis Fast random access. Datalab. BigQuery. Lab: Build machine learning dataset. Machine Learning Machine Learning with TensorFlow. Lab: Carry out ML with TensorFlow Pre-built models for common needs. Lab: Employ ML APIs. Data Processing Architectures Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow. Reference architecture for real-time and batch data processing. Summary Why GCP? Where to go from here Additional Resources Additional course details: Nexus Humans Google Cloud Platform Big Data and Machine Learning Fundamentals training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Google Cloud Platform Big Data and Machine Learning Fundamentals course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Data Analysis: Data Analysis Training Have you ever wondered how companies get insights from massive volumes of data to stay competitive and make wise decisions? If so, then participate in our exclusive Data Analysis: Data Analysis Course. This Data Analysis Course describes the fundamentals of data, statistics, and an introduction to Data Analysis. How to get data and where to find it is explained in the Data Analysis Course. Moreover, this Data Analysis Course covers data cleansing, preprocessing, and exploratory data analysis (EDA). Additionally, the Data Analysis Course provides an introduction to Python and Excel for Data Analysis. This thorough Data Analysis Course includes lessons on data wrangling with Pandas (python) and data visualisation using Matplotlib and Seaborn (python). Enrol in our Data Analysis Course to study the fundamentals of statistical analysis and machine learning. Main Course: Data Analysis (Data Analytics) Training Free Courses included with Data Analysis: Data Analysis Training Course: Course 01: Minute Taking Course 02: GDPR Course 03: Cyber Security [ Note: Free PDF certificate as soon as completing the Data Analysis: Data Analysis Training Course] Data Analysis: Data Analysis Training Online This Data Analysis (Data Analytics) Training consists of 12 modules. Curriculum of Data Analysis (Data Analytics) Training Course Module 1: Introduction to Data Analytics Module 2: Basics of Data and Statistics Module 3: Data Collection and Sources Module 4: Data Cleaning and Preprocessing Module 5: Exploratory Data Analysis (EDA) Module 6: Introduction to Excel for Data Analytics Module 7: Introduction to Python for Data Analytics Module 8: Data Wrangling with Pandas (Python) Module 9: Data visualisation with Matplotlib and Seaborn (Python) Module 10: Introduction to Basic Statistical Analysis Module 11: Introduction to Machine Learning Module 12: Capstone Project - Exploratory Data Analysis Assessment Method of Data Analysis (Data Analytics) Training Course After completing Data Analysis: Data Analysis Training Course, you will get quizzes to assess your learning. You will do the later modules upon getting 60% marks on the quiz test. Apart from this, you do not need to sit for any other assessments. Certification of Data Analysis (Data Analytics) Training Course After completing the Data Analysis: Data Analysis Training Course, you can instantly download your certificate for FREE. The hard copy of the certification will also be delivered to your doorstep via post, which will cost £13.99. Who is this course for? Data Analysis: Data Analysis Training Online For business professionals, entrepreneurs, or anybody else looking to have a thorough grasp of data analysis in a commercial setting, this Data Analysis Course is ideal. Requirements Data Analysis: Data Analysis Training Online To enrol in this Data Analysis: Data Analysis Training Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Data Analysis Training Course. Be energetic and self-motivated to complete our Data Analysis Training Course. Basic computer Skill is required to complete our Data Analysis Training Course. If you want to enrol in our Data Analysis Training Course, you must be at least 15 years old. Career path Data Analysis: Data Analysis Training Online This Data Analysis Course will assist you in obtaining positions as a business analyst, marketing analyst, data analysis, and in related fields.

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Machine literacy in data wisdom is a fleetly expanding discipline and now is the crucial element. This groundbreaking field equips computers and systems with the capacity to learn from data and ameliorate their performance over time without unequivocal programming. Statistical ways are employed to train algorithms to produce groups or prognostications and to find significant findings in data mining systems. immaculately, the conclusions made from these perceptivity impact crucial growth pointers in operations and companies. What's Machine Learning? . Machine learning classes in pune The machine literacy term was chased by Arthur Samuel in 1959. It's the discipline solely concentrated on studying and erecting tools and ways that can let machines learn. These styles use data to enhance the computer performance of a particular set of tasks. Machine literacy algorithms induce prognostications or possibilities and produce a model grounded on data samples, also called training data. There's a need for machine literacy as these algorithms are applied in a broad range of operations, for illustration, computer vision, dispatch filtering, speech recognition, husbandry, and drugs, where it's a challenge to produce traditional algorithms that can negotiate the needed tasks. orders in Machine Learning Being such a vast and complicated field, machine literacy is divided into three different orders machine literacy orders Supervised literacy – In this system, the algorithm is trained using data that has been labeled and in which the target variable or asked result is known. Once trained, the algorithm may make prognostications grounded on unidentified information by learning how to associate input variables with the willed affair. Unsupervised literacy – In this case, the algorithm is trained on unlabeled data, and its thing is to discover structures or patterns within the data without having a specific target variable in mind. Common unsupervised literacy tasks include dimensionality reduction and clustering. underpinning literacy – An algorithm is trained via relations with the terrain in this type of literacy. The algorithm learns how to operate in order to maximize a price signal or negotiate a particular ideal. Through prices or penalties, it receives feedback that helps it upgrade its decision-making process. Artificial Intelligence and Machine Learning Artificial intelligence( AI) is divided into several subfields, and machine literacy( ML) is one of them. In order to produce intelligent machines that can pretend mortal intelligence, a variety of methodologies, approaches, and technologies are used. This notion is known as artificial intelligence( AI). The development of ways and models that allow computers to acquire knowledge from data and make recommendations or judgments without unequivocal programming is the focus of machine literacy( ML). Some academics were interested in the idea of having machines learn from data in the early stages of AI as an academic field. They tried to approach the issue using colorful emblematic ways and neural networks. They were primarily perceptrons, along with other models that were ultimately discovered to be reimaginings of the generalized direct models of statistics. For this case, you aim to make a system secerning cows and tykes. With the AI approach, you'll use ways to make a system that can understand the images with the help of specific features and rules you define. Machine literacy models will bear training using a particular dataset of pre-defined images. You need to give numerous farmlands of cows and tykes with corresponding markers. Why is Machine Learning Important? Machine literacy is an abecedarian subfield of artificial intelligence that focuses on assaying and interpreting patterns and structures in data. It enables logic, literacy, and decision-making outside of mortal commerce. The significance of machine literacy is expanding due to the extensively more expansive and more varied data sets, the availability and affordability of computational power, and the availability of high-speed internet. It facilitates the creation of new products and provides companies with a picture of trends in consumer geste and commercial functional patterns. Machine literacy is a high element of the business operations of numerous top enterprises, like Facebook, Google, and Uber. Prophetic Analytics Machine learning course in pune Machine literacy makes prophetic analytics possible by using data to read unborn results. It's salutary in the fields of finance, healthcare, marketing, and logistics. Associations may prognosticate customer growth, spot possible troubles, streamline operations, and take visionary action to ameliorate results using prophetic models. Personalization and recommendation systems Machine literacy makes recommendation systems and substantiated gests possible, impacting every aspect of our diurnal lives. Platforms like Netflix, Amazon, and Spotify use machine literacy algorithms to comprehend stoner preferences and offer substantiated recommendations. Personalization boosts stoner pleasure and engagement while promoting business expansion. Image and speech recognition Algorithms for machine literacy are particularly good at jobs like speech and picture recognition. Deep literacy, a branch of ML, has converted computer vision and natural language processing. It makes it possible for machines to comprehend, dissect, and produce visual and audio input. This technology is helpful for driverless vehicles, surveillance, medical imaging, and availability tools, among other effects. Machine learning training in pune

Course Overview: The "FinTech and Big Data Analytics" course provides an in-depth exploration of the dynamic intersection between financial technology (FinTech) and big data. Learners will gain essential knowledge about the innovative solutions disrupting the financial services industry, such as cryptocurrencies, insurtech, and regtech. The course offers insights into the tools, technologies, and trends shaping the future of finance, with a specific focus on how big data analytics is transforming business models and decision-making. By the end of the course, learners will have a comprehensive understanding of FinTech's growth and its applications, enabling them to make informed decisions in this rapidly evolving field. Course Description: This course delves deeper into the core concepts of financial technology and big data, exploring the impact of FinTech innovations on traditional financial systems. Topics covered include the rise of cryptocurrencies, regulatory technology (RegTech), the development of insurance technologies (InsurTech), and the use of big data in reshaping business strategies. Learners will explore the key technologies that drive FinTech, such as blockchain, artificial intelligence (AI), and machine learning, and learn how they enable data-driven decision-making in finance. The course prepares learners for the evolving future of FinTech, equipping them with the necessary skills to understand and navigate this transformative landscape. Course Modules: Module 01: Introduction to Financial Technology – FinTech Module 02: Exploring Cryptocurrencies Module 03: RegTech Module 04: Rise of InsurTechs Module 05: Big Data Basics: Understanding Big Data Module 06: The Future of FinTech (See full curriculum) Who is this course for? Individuals seeking to understand the financial technology landscape. Professionals aiming to advance their careers in the rapidly evolving FinTech sector. Beginners with an interest in emerging financial technologies and data analytics. Entrepreneurs looking to innovate within the financial services industry. Career Path: Financial Analyst FinTech Specialist Data Analyst in Financial Services Blockchain Developer RegTech Consultant InsurTech Specialist Big Data Analyst in Finance

Data Analysis: Data Analysis Course Would you like to acquire the skills and self-assurance necessary to make wise choices and successfully traverse the intricate and ever-changing realm of data analysis? Enrol in our Data Analysis Course. The fundamentals of data, statistics, and an introduction to data analysis are all covered in this data analysis course. The how-to of data collection and its sources are explained in the Data Analysis Course. This Data Analysis Course teaches preprocessing, data cleansing, and exploratory data analysis (EDA). An overview of Excel and Python for data analysis is explained in this Data Analysis Course. This extensive Data Analysis course includes lessons on data wrangling with Pandas (Python) and data visualisation using Matplotlib and Seaborn (Python). So, quickly join our Data Analysis Course to learn the fundamentals of machine learning and statistical analysis! Special Offers with free gifts for this Data Analysis: Data Analysis Course This Data Analysis Course course includes a FREE PDF Certificate. Lifetime access to this Data Analysis Course course Instant access to this Data Analysis Course course Get FREE Tutor Support to this Data Analysis Course Course Learning Outcome of Data Analysis Course This Data Analysis Course will help you learn about: Introduction to data analysis, basics of data, and statistics. Data Analysis Course explains how to collect data and its sources. Data cleaning, processing, and exploratory data analysis (EDA) are included in this Data Analysis Course. This Data Analysis Course describes an introduction to Excel for Data Analysis and Python for Data Analysis. Data Wrangling with Pandas (Python) and Data Visualisation with Matplotlib and Seaborn (Python) are parts of this comprehensive Data Analysis Course. With the help of this Data Analysis Course, you will learn the basics of statistical analysis and machine learning. Data Analysis: Data Analysis Course Embark on a transformative journey with our Data Analysis course, designed for beginners. Dive deep into the world of data analysis, mastering essential techniques and tools. Gain practical skills in Data Analysis, empowering you to unlock insights and drive informed decisions. Start your Data Analysis journey today! Who is this course for? Data Analysis: Data Analysis Course Anyone looking to have a thorough grasp of data analysis in a commercial setting should take this Data Analysis: Data Analysis Course. Requirements Data Analysis: Data Analysis Course To enrol in this Data Analysis: Data Analysis Course, students must fulfil the following requirements. To join in our Data Analysis: Data Analysis Course, you must have a strong command of the English language. To successfully complete our Data Analysis: Data Analysis Course, you must be vivacious and self driven. To complete our Data Analysis: Data Analysis Course, you must have a basic understanding of computers. A minimum age limit of 15 is required to enrol in this Data Analysis: Data Analysis Course. Career path Data Analysis: Data Analysis Course With the assistance of this Data Analysis Course, you can obtain work as a data analyst, business analyst, marketing analyst, or in related fields.

Let’s face it—no one enjoys spending hours battling stubborn weeds that just keep coming back. Whether you're managing a garden, farm, or green space, knowing your enemy is half the battle. This Weed Recognition and Management Course gives you the upper hand, helping you spot the troublemakers before they spread and take over. You'll learn how to identify common (and not-so-common) weeds by their features, growth habits, and seasonal patterns—saving you time, effort, and a good bit of frustration. This course goes beyond pulling up dandelions and hoping for the best. It offers smart strategies for weed control, covering chemical, biological, and cultural methods used across the UK. Whether you're new to plant care or already knee-deep in the gardening game, the course is clear, informative, and easy to follow. Everything is online, meaning you can learn at your own pace without muddy boots or sunburn. Key Features CPD Accredited FREE PDF + Hardcopy certificate Fully online, interactive course Self-paced learning and laptop, tablet and smartphone-friendly 24/7 Learning Assistance Discounts on bulk purchases Course Curriculum Module 01: Introduction to Weeds and Their Impact Module 02: Weed Identification Module 03: Weed Biology and Ecology Module 04: Physical and Cultural Weed Control Methods Module 05: Chemical Weed Control Methods Module 06: Integrated Weed Management Learning Outcomes Recognize diverse weed species through advanced identification techniques. Understand the intricate biology and ecology of weeds for effective management. Apply physical and cultural methods to control weeds in various environments. Implement chemical weed control strategies with precision and environmental consciousness. Master integrated weed management for a holistic and sustainable approach. Develop expertise in weed recognition and management for practical application. Accreditation This course is CPD Quality Standards (CPD QS) accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Certificate After completing this course, you will get a FREE Digital Certificate from Training Express. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Agriculture professionals seeking advanced weed management knowledge. Environmentalists aiming to contribute to ecosystem preservation. Farmers looking to enhance crop yield through effective weed control. Horticulturists interested in sustainable and integrated weed management. Landscapers desiring in-depth knowledge of weed dynamics. Conservationists striving to protect native flora and fauna. Botanists keen on understanding the ecological impact of different weed species. Individuals passionate about sustainable agriculture and environmental stewardship. Career path Agricultural Consultant Environmental Scientist Crop Protection Specialist Ecological Restoration Technician Horticulture Manager Conservation Officer Certificates Digital certificate Digital certificate - Included Once you've successfully completed your course, you will immediately be sent a FREE digital certificate. Hard copy certificate Hard copy certificate - Included Also, you can have your FREE printed certificate delivered by post (shipping cost £3.99 in the UK). For all international addresses outside of the United Kingdom, the delivery fee for a hardcopy certificate will be only £10. Our certifications have no expiry dates, although we do recommend that you renew them every 12 months.