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 Yishun

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 Yishun, chennai and europe countries. You can find many jobs for freshers related to the job positions in Yishun.

  • 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 Yishun
Data Science Effectively analyze both organized and unstructured data Create strategies to address company issues. Cleaning and validating data to ensure that it is accurate and consistent. Exercises, tasks, and projects that are completed in real-time 24 hours a day, 7 days a week, A large network of like-minded newbies, an industry-recognized intellipaat credential, and individualized employment support Several data scientist responsibilities are listed below. The Data Science Process, Communicating with Stakeholders, Software Engineering Practices, Object-Oriented Programming, Web Development, ETL Pipelines, Natural Language Processing, Machine Learning Pipelines, Experiment Design, Statistical Concerns of Experimentation, A/B Testing, and Introduction to Recommendation Engines are some of the topics covered in. This finest Data Science course was built with the needs of businesses in mind when it comes to the field of Data Science. You'll have a personal mentor who will keep track of your development. Today's Data Scientists must possess a wide range of abilities, including the ability to work with large amounts of data, parse that data, and translate it into an easily comprehensible format from which business insights may be drawn. Experts provide immersive online instructor-led seminars. There are numerous reasons why you should take this course. A data scientist is a person who uses a variety of procedures, methods, systems, and algorithms to analyze data to provide actionable insights.

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 Yishun

  • KumonLearningCentre-Yishun-JunctionNine | Location details: 18 Yishun Avenue 9 Junction Nine #02-31, Singapore 768897 | Classification: Education center, Education center | Visit Online: kumon.sg | Contact Number (Helpline): +65 8879 5339
  • YourSempreMusic | Location details: 106 Yishun Ring Road #01-155, 2nd Floor, Singapore 760106 | Classification: Music school, Music school | Visit Online: yoursempremusic.com.sg | Contact Number (Helpline): +65 8878 1211
  • MindsYishunTraining&DevelopmentCentre | Location details: Singapore | Classification: School, School | Visit Online: | Contact Number (Helpline):
  • AGraderLearningCentre-Yishun | Location details: 930 Yishun Avenue 2 #03-37 (S)769098 Northpoint City (North Wing, Singapore 769098 | Classification: Learning center, Learning center | Visit Online: agrader.sg | Contact Number (Helpline): +65 9088 1928
  • MPMEducationalInstitute-Yishun | Location details: 921 Yishun Central 1, Singapore 760921 | Classification: Educational consultant, Educational consultant | Visit Online: | Contact Number (Helpline): +65 9233 1772
  • YishunTutorEnglishMathsScienceTuitionCentre | Location details: 664 Yishun Ave 4, Singapore 760664 | Classification: Educational institution, Educational institution | Visit Online: yishuntutor.com | Contact Number (Helpline): +65 8222 6327
  • LyTa&Consultants | Location details: 1 Yishun Industrial Street 1 A, #07-27 POSH Bizhub, Singapore 768160 | Classification: Educational consultant, Educational consultant | Visit Online: lyta.sg | Contact Number (Helpline): +65 6876 7923
  • LifesavingCourse.com|LifeguardTrainingSchool | Location details: 351 Yishun Ave 3, Singapore 769057 | Classification: School, School | Visit Online: | Contact Number (Helpline): +65 9006 0074
  • THOTHSTUDYINN(StudentCare/Tuition/Enrichment) | Location details: Blk #01-39, 731 Yishun Street 72, Singapore 760731 | Classification: Educational institution, Educational institution | Visit Online: facebook.com | Contact Number (Helpline): +65 9005 0063
  • NorthlandSecondarySchool | Location details: 3 Yishun Street 22, Singapore 768578 | Classification: High school, High school | Visit Online: northlandsec.moe.edu.sg | Contact Number (Helpline): +65 6257 6781
  • KenTuitionCentre-Yishun | Location details: #01-1003 Yishun Ring Rd, #2nd Level Block 256, Singapore 760256 | Classification: Education center, Education center | Visit Online: | Contact Number (Helpline): +65 6757 3943
  • ExponentialLearningCentre(YishunTuition) | Location details: Blk 619 Yishun Ring Rd, #01-3226, Singapore 760619 | Classification: Education center, Education center | Visit Online: facebook.com | Contact Number (Helpline): +65 9745 2364
  • TheLittleArtsAcademy-NorthCampusI | Location details: 930 North Wing Yishun Ave 2 #03-38 Northpoint City, Singapore 769098 | Classification: Art school, Art school | Visit Online: thelittleartsacademy.sg | Contact Number (Helpline): +65 6513 3013
  • MyFirstSkoolAtBlk612Yishun | Location details: Blk 612 Yishun Street 61, #01-193, Singapore 760612 | Classification: Preschool, Preschool | Visit Online: myfirstskool.com | Contact Number (Helpline): +65 6509 7887
  • KenTuitionCentre-Yishun | Location details: #01-1003 Yishun Ring Rd, #2nd Level Block 256, Singapore 760256 | Classification: Education center, Education center | Visit Online: | Contact Number (Helpline): +65 6757 3943
  • StepUpLearning&Dance@SAFRAYishun | Location details: 60 Yishun Ave 4, #01-02, Singapore 769027 | Classification: Dance school, Dance school | Visit Online: stepup.sg | Contact Number (Helpline): +65 6758 3835
 courses in Yishun
Geoff Malone, mastermind behind Yishun 10(b. 928 Laksa Blk 928 Yishun Central 1# 01- 157 This popular laksa( racy pate dish) cube has been around since the 1990s. KEW ONG YAH TEMPLE AND HONG SAN SEE tabernacle This tabernacle is made up of a many tabernacles which were formerly located in Nee Soon, including Chan Chu Kang Tua Pek Kong Temple, Hong San See Temple and Kew Ong Yah Temple. The tabernacle played an important part in the religious and social life of the vill also, furnishing burial services for the indigent and acting as a place for townies to socialise. In another part of the vill, a townie went into a reverie . “ He was a man devoted to the cause of his fellow workers anyhow of race or religion. In 1986, the demesne was refurbished and periodic prayer observances are held then to flash back these settlers. According to the tabernacle trustees, the tabernacle began when a family in the vill transferred the statue of its deity for restoration, informing the deity to return at a specific date and time. Due to urbanisation, Nam Hong Siang Theon Temple moved to Yishun in 1984, participating the point with two other tabernacles, Seng Pang Tua Pek Kong Keng and Ho Peck San Temple. By the end of 1993, the$ 37 million,,552- seat Yishun 10, Asia’s first Cineplex, a movie theatre with several amphitheaters, had proven all critics awry after clocking further than three million callers since the day it opened! Yishun 10 was the concoction of Golden Village, a common adventure between Hong Kong company Golden Harvest and Australian company Village Roadshow.

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