Data Science Training by Experts

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Data Science - Syllabus, Fees & Duration

MODULE 1

  • The Data Science Process
  • Apply the CRISP-DM process to business applications
  • Wrangle, explore, and analyze a dataset
  • Apply machine learning for prediction
  • Apply statistics for descriptive and inferential understanding
  • Draw conclusions that motivate others to act on your results

MODULE 2

  • Communicating with Stakeholders
  • Implement best practices in sharing your code and written summaries
  • Learn what makes a great data science blog
  • Learn how to create your ideas with the data science community

MODULE 3

  • Software Engineering Practices
  • Write clean, modular, and well-documented code
  • Refactor code for efficiency
  • Create unit tests to test programs
  • Write useful programs in multiple scripts
  • Track actions and results of processes with logging
  • Conduct and receive code reviews

MODULE 4

  • Object Oriented Programming
  • Understand when to use object oriented programming
  • Build and use classes
  • Understand magic methods
  • Write programs that include multiple classes, and follow good code structure
  • Learn how large, modular Python packages, such as pandas and scikit-learn, use object oriented programming
  • Portfolio Exercise: Build your own Python package

MODULE 5

  • Web Development
  • Learn about the components of a web app
  • Build a web application that uses Flask, Plotly, and the Bootstrap framework
  • Portfolio Exercise: Build a data dashboard using a dataset of your choice and deploy it to a web application

MODULE 6

  • ETL Pipelines
  • Understand what ETL pipelines are
  • Access and combine data from CSV, JSON, logs, APIs, and databases
  • Standardize encodings and columns
  • Normalize data and create dummy variables
  • Handle outliers, missing values, and duplicated data
  • Engineer new features by running calculations • Build a SQLite database to store cleaned data

MODULE 7

  • Natural Language Processing
  • Prepare text data for analysis with tokenization, lemmatization, and removing stop words
  • Use scikit-learn to transform and vectorize text data
  • Build features with bag of words and tf-idf
  • Extract features with tools such as named entity recognition and part of speech tagging
  • Build an NLP model to perform sentiment analysis

MODULE 8

  • Machine Learning Pipelines
  • Understand the advantages of using machine learning pipelines to streamline the data preparation and modeling process
  • Chain data transformations and an estimator with scikit- learn’s Pipeline
  • Use feature unions to perform steps in parallel and create more complex workflows
  • Grid search over pipeline to optimize parameters for entire workflow
  • Complete a case study to build a full machine learning pipeline that prepares data and creates a model for a dataset

MODULE 9

  • Experiment Design
  • Understand how to set up an experiment, and the ideas associated with experiments vs. observational studies
  • Defining control and test conditions
  • Choosing control and testing groups

MODULE 10

  • Statistical Concerns of Experimentation
  • Applications of statistics in the real world
  • Establishing key metrics
  • SMART experiments: Specific, Measurable, Actionable, Realistic, Timely

MODULE 11

  • A/B Testing
  • How it works and its limitations
  • Sources of Bias: Novelty and Recency Effects
  • Multiple Comparison Techniques (FDR, Bonferroni, Tukey)
  • Portfolio Exercise: Using a technical screener from Starbucks to analyze the results of an experiment and write up your findings

MODULE 12

  • Introduction to Recommendation Engines
  • Distinguish between common techniques for creating recommendation engines including knowledge based, content based, and collaborative filtering based methods.
  • Implement each of these techniques in python.
  • List business goals associated with recommendation engines, and be able to recognize which of these goals are most easily met with existing recommendation techniques.

MODULE 13

  • Matrix Factorization for Recommendations
  • Understand the pitfalls of traditional methods and pitfalls of measuring the influence of recommendation engines under traditional regression and classification techniques.
  • Create recommendation engines using matrix factorization and FunkSVD
  • Interpret the results of matrix factorization to better understand latent features of customer data
  • Determine common pitfalls of recommendation engines like the cold start problem and difficulties associated with usual tactics for assessing the effectiveness of recommendation engines using usual techniques, and potential solutions.

Download Syllabus - Data Science
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Data Science Jobs in Surrey

Enjoy the demand

Find jobs related to Data Science in search engines (Google, Bing, Yahoo) and recruitment websites (monsterindia, placementindia, naukri, jobsNEAR.in, indeed.co.in, shine.com etc.) based in Surrey, chennai and europe countries. You can find many jobs for freshers related to the job positions in Surrey.

  • Data Scientist
  • Data Analyst
  • Data Engineer
  • Data Storyteller
  • Machine Learning Scientist
  • Machine Learning Engineer
  • Business Intelligence Developer
  • Database Administrator
  • ML Engineer
  • Computer Vision Engineer

Data Science Internship/Course Details

Data Science internship jobs in Surrey
Data Science To succeed as a data scientist, you must, nevertheless, make a particular effort to apply soft skills. This finest Data Science course was built with the needs of businesses in mind when it comes to the field of Data Science. Effectively analyze both organized and unstructured data Create strategies to address company issues. A Data Scientist is a highly skilled someone with advanced mathematical, statistical, scientific, analytical, and technical abilities who can prepare, clean, and validate organized and unstructured data for industries to utilize in making better decisions. A data scientist is a person who uses a variety of procedures, methods, systems, and algorithms to analyze data to provide actionable insights. To find trends and patterns, use algorithms and modules. . Experts provide immersive online instructor-led seminars. Identify and collect data from data sources. Cleaning and validating data to ensure that it is accurate and consistent.

List of All Courses & Internship by TechnoMaster

Success Stories

The enviable salary packages and track record of our previous students are the proof of our excellence. Please go through our students' reviews about our training methods and faculty and compare it to the recorded video classes that most of the other institutes offer. See for yourself how TechnoMaster is truly unique.

List of Training Institutes / Companies in Surrey

  • SafeSoftwareInc. | Location details: 9639 137a St #1200, Surrey, BC V3T 0M1 | Classification: Software company, Software company | Visit Online: safe.com | Contact Number (Helpline): (604) 501-9985
  • LondonAndSurreyGasServicesLtd | Location details: 423 Kingston Rd, Wimbledon Chase, London SW20 8JR, United Kingdom | Classification: Heating contractor, Heating contractor | Visit Online: londonsurreygasservices.org.uk | Contact Number (Helpline): +44 20 8543 3900
  • A-GradeTrainingServicesLtd | Location details: Trelawny House, Surrey St, St Paul's, Bristol BS2 8PS | Classification: Training provider, Training provider | Visit Online: | Contact Number (Helpline): 0845 003 0895
 courses in Surrey
[3] In the 2020 provincial election, the BC NDP stored as a minimum their formerly six elected MLAs (probably seven), even as the quantity of MLAs for the BC Liberals may have among and 3. Mainly a suburban town, Surrey is the province`s 2nd-biggest with the aid of using populace after Vancouver and the third-biggest with the aid of using location after Abbotsford and Prince George. Surrey paperwork an crucial a part of Metro Vancouver as it's far the second one biggest town withinside the region, albeit even as additionally serving because the secondary monetary middle of the metropolitan location. Settlers arrived first in Cloverdale and elements of South Surrey, ordinarily to farm, fish, harvest oysters, or installation small stores. Once the Pattullo Bridge become erected in 1937, the manner become open for Surrey to expand. [15][16] Ethnicity Within the City of Surrey itself characteristic many neighbourhoods which includes City Centre, Whalley, Newton, Guildford, Fleetwood, Cloverdale and South Surrey. In the Eighties and 1990s, the town witnessed extraordinary growth, as humans from one-of-a-kind elements of Canada and the world, especially Asia, started out to make the municipality their domestic. Each neighbourhood is particular and consists of ethnically numerous populations. In 2013, it become projected to surpass the town of Vancouver because the maximum populous town in BC in the following 10 to twelve years. It is a member municipality of the Metro Vancouver nearby district and metropolitan location.

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