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DATA SCIENTIST
Specialization | 150 Course Series

This Data Scientist Training Course includes 150 courses with 608+ hours of video tutorials and One year access. You will also get verifiable certificates (unique certification number and your unique URL) when you complete each of them. This comprehensive course will teach you programming languages, machine learning, Hadoop, Business analytics, Data Visualization and other important analytics concepts.

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What you'll get

  • 608+ Hours
  • 150 Courses
  • Course Completion Certificates
  • One year access
  • Self-paced Courses
  • Technical Support
  • Mobile App Access
  • Case Studies

Synopsis

  • Courses: You get access to all 150 courses, Projects bundle. You do not need to purchase each course separately
  • Hours: 608+ Video Hours
  • Core Coverage: This Data Scientist course will help you learn data science using R, Python, machine learning, artificial intelligence, big data & Hadoop, predictive modeling, business analytics, data visualization, and others.
  • Course Validity: One year access
  • Eligibility: Anyone serious about learning data science and wants to make a career in analytics
  • Pre-Requisites: Basic knowledge of data and analytics
  • What do you get? Certificate of Completion for each of the 150 courses and projects
  • Certification Type: Course Completion Certificates
  • Verifiable Certificates? Yes, you get verifiable certificates for each course with a unique link. These link can be included in your resume or LinkedIn profile to showcase your enhanced skills

Content

  • MODULE 1: Data Science with Python Essentials Training

    Courses No. of Hours Certificates Details
    Machine Learning with Python 20245h 17m✔
    Machine Learning with Python Case Study - Covid19 Mask Detector2h 05m✔
    Deep Learning: Automatic Image Captioning for Social Media with Tensorflow2h 23m✔
    AI Machine Learning in Python8h 37m✔
    Predictive Analytics and Modeling with Python8h 26m✔
    Matplotlib for Python Data Visualization - Beginners4h 12m✔
    Matplotlib for Python Data Visualization - Intermediate2h 53m✔
    Matplotlib for Python Data Visualization - Advanced6h 37m✔
    Pandas with Python Tutorial5h 56m✔
    NumPy and Pandas Python4h 8m✔
    Pandas Python Case Study - Data Management for Retail Dataset3h 22m✔
    Python Case Study - Sentiment Analysis57m✔
    Data Science with Python4h 18m✔
    Artificial Intelligence with Python - Beginner Level2h 51m✔
    Artificial Intelligence with Python - Intermediate Level4h 34m✔
    AI Artificial Intelligence & Predictive Analysis with Python6h 15m✔
    Video Analytics using OpenCV and Python Shells2h 13m✔
    Machine Learning using Python3h 26m✔
    Statistics Essentials with Python3h 23m✔
    Project on Tensorflow - Implementing Linear Model with Python1h 46m✔
    Project - Data Analytics with Data Exploration Case Study5h 7m✔
    Random Forest Algorithm using Python1h 27m✔

  • MODULE 2: Data Science with R & Python Essentials Training

    Courses No. of Hours Certificates Details
    Seaborn Python - Beginners2h 28m✔
    Seaborn Python - Intermediate1h 18m✔
    Seaborn Python - Advanced1h 56m✔
    PySpark Python - Beginners2h 16m✔
    PySpark Python - Intermediate2h 02m✔
    PySpark Python - Advanced1h 18m✔
    Machine Learning Python Case Study - Diabetes Prediction1h 02m✔
    R Studio UI and R Script Basics4h 13m✔
    R Programming for Data Science | A Complete Courses to Learn5h 7m✔
    Logistic Regression & Supervised Machine Learning with R4h 14m✔
    Decision Trees Modeling using R1h 4m✔
    Project on ML - Churn Prediction Model using R Studio1h 22m✔
    Financial Analytics in R - Beginners3h 53m✔
    Financial Analytics in R - Intermediate1h 28m✔
    Financial Analytics in R - Advanced1h 35m✔
    R for Finance - Beginners to Beyond2h 17m✔
    Comprehensive Course on R3h 54m✔
    Time Series Analysis and Forecasting using R4h 34m✔
    Project - Fraud Analytics using R2h 34m✔
    Project - Marketing Analytics using R and Microsoft Excel2h 9m✔
    Machine Learning with R20h 25m✔
    Case Study - Customer Analytics using Tableau and R2h 7m✔
    Case Study - Pricing Analytics using Tableau and R2h 39m✔
    Business Analytics using R - Hands-on!16h 21m✔
    Project - Market Basket Analysis in R37m✔
    Project - Hypothesis Testing using R3h 6m✔
    Data Visualization with R Shiny - The Fundamentals39m✔
    Data Science with R6h 2m✔
    R Studio Anova Techniques Course2h 18m✔

  • MODULE 3: Data Science with SAS Essentials Training

    Courses No. of Hours Certificates Details
    SAS Business Analytics for Beginners10h 45m✔
    Predictive Analytics & Modeling with SAS9h 19m✔
    Quantitative Finance with SAS3h 29m✔
    SAS Statistics8h 18m✔
    SAS ODS (Output Delivery System)9h 36m✔
    SAS PROC SQL13h 49m✔
    SAS Macros7h 25m✔
    SAS Advanced Analytics12h 22m✔
    SAS Graph2h 1m✔
    SAS DS24h 59m✔
    SAS SQL3h 01m✔
    SAS Practical - Macros5h 5m✔
    SAS Advanced Programming10h 7m✔
    SAS Categorical Data Analysis7h 16m✔
    Certified SAS Base Programmer12h 2m✔
    SAS Features for Starters1h 5m✔
    SAS PROC SQL Features1h 49m✔

  • MODULE 4: Big Data & Hadoop

    Courses No. of Hours Certificates Details
    Big Data and Hadoop Training | Online Hadoop Course2h 2m✔
    Hadoop Architecture and HDFS6h 13m✔
    MapReduce - Beginners3h 01m✔
    MapReduce - Advanced5h 35m✔
    Hive - Beginners2h 47m✔
    Hive - Advanced5h 11m✔
    PIG - Beginners2h 1m✔
    PIG - Advanced2h 13m✔
    NoSQL Fundamentals2h 01m✔
    Mahout3h 5m✔
    Apache Oozie2h 11m✔
    Apache Storm2h 4m✔
    Apache Spark - Beginners1h 4m✔
    Apache Spark - Advanced5h 49m✔
    Splunk Fundamentals8h 33m✔
    Splunk Advanced 01 - Knowledge Objects9h 29m✔
    Splunk Advanced 02 - Administration39h ✔

  • MODULE 5: Learning from Projects & Practicals

    Courses No. of Hours Certificates Details
    Project on Hadoop - Sales Data Analysis47m✔
    Project on Hadoop - Tourism Survey Analysis53m✔
    Project on Hadoop - Faculty Data Management35m✔
    Project on Hadoop - E-Commerce Sales Analysis35m✔
    Project on Hadoop - Salary Analysis49m✔
    Project on Hadoop - Health Survey Analysis using HDFS56m✔
    Project on Hadoop - Traffic Violation Analysis1h 25m✔
    Project on Hadoop - Analyze Loan Dataset using PIG/MapReduce2h 33m✔
    Project on Hadoop - Case Study on Telecom Industry using HIVE2h 2m✔
    Project on Hadoop - Customers Complaints Analysis using HIVE/MapReduce53m✔
    Project on Hadoop - Social Media Analysis using HIVE/PIG/MapReduce/Sqoop3h 34m✔
    Project on Hadoop - Sensor Data Analysis using HIVE/PIG5h 26m✔
    Project on Hadoop - Youtube Data Analysis using PIG/MapReduce3h 02m✔
    Hadoop and HDFS Fundamentals on Cloudera1h 22m✔
    Project on Hadoop - Log Data Analysis1h 32m✔
    SPSS 2024 - Beginners1h 07m✔
    SPSS 2024 - Advanced5h 19m✔
    Advanced SPSS Project: Impact of EMI on Home Loan43m✔
    Advanced SPSS Project: Impact of Total Turnover in Equity Market58m✔
    Advanced SPSS Project: Impact of Trade Data in Equity Market46m✔
    SPSS GUI and Applications1h 13m✔
    SPSS - Correlation Techniques1h 8m✔
    Linear Regression & Supervised Learning with SPSS3h 07m✔
    SPSS - Multiple Regression Modeling2h 34m✔
    Logistic Regression & Supervised Learning using SPSS2h 37m✔
    SPSS - Multinomial Regression2h 2m✔
    SPSS GUI for Statistical Analysis2h ✔
    Tableau Desktop Training 20244h 21m✔
    Tableau Project-Creating Dashboard and Stories For Financial Markets2h 08m✔
    Tableau Project - Russo-Ukraine War A Data Analytical Review1h 02m✔
    Tableau4h 7m✔
    BI Tools and Tableau Analytics5h 38m✔
    Business Intelligence with Tableau5h 43m✔
    Tableau Features Hands-on!5h 32m✔
    Tableau Practical - Super Store Business Requirements45m✔
    Analytics using Tableau9h 28m✔

  • MODULE 6: Minitab and MATLAB

    Courses No. of Hours Certificates Details
    Minitab for Beginners - 20241h 15m✔
    Advanced Minitab Training - 20244h 39m✔
    Minitab Practical - Impact of Predictors on Response1h 35m✔
    Statistical Analysis using Minitab - Beginners to Beyond4h 21m✔
    Minitab GUI and Descriptive Statistics2h 43m✔
    ANOVA in Minitab52m✔
    Correlation Techniques in Minitab2h 18m✔
    Project on Minitab - Regression Modeling9h 36m✔
    Minitab Predictive Modeling using Excel55m✔
    MATLAB - Beginners3h 9m✔
    MATLAB - Intermediate47m✔
    MATLAB - Advanced4h 1m✔

  • MODULE 7: Database & SQL

    Courses No. of Hours Certificates Details
    Oracle SQL17h 32m✔
    Oracle PLSQL13h 2m✔
    Oracle DBA 19h 27m✔
    Machine Learning ZERO to HERO - Hands-on with Tensorflow13h 03m✔
    Deep Learning ZERO to HERO - Hands-on with Python11h 17m✔
    Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression2h 07m✔
    Project on R - HR Attrition and Analytics2h 4m✔
    Logistic Regression using SAS Stat4h 26m✔
    Linear Regression & Supervised Learning in Python2h 28m✔
    Logistic Regression & Supervised Machine Learning in Python2h 6m✔
    Project on R - Card Purchase Prediction2h 28m✔
    Develop a Movie Recommendation Engine51m✔
    Random Forest Techniques and R - Employee Attrition Prediction1h 6m✔
    Predictive Analytics Model for Term Deposit Investment using CART Algorithm1h 38m✔
    Poisson Regression with SAS Stat2h 21m✔
    Machine Learning Project using Caret in R1h 58m✔
    Sales Forecasting using Time Series Analysis in Python2h 13m✔

Sample Certificate

Course Certification

Requirements

  • Basics of Linear Algebra: Data Science deals with vectors, matrices, and their operations. If you don’t have a clear picture, it would be great if you could refresh it and then take this data scientist training. It will help you once you go deeper into data science-related algorithms.
  • Coding background: Learning languages like R and Python to explore datasets and analyze them goes way easier if you have a programming background. It could be C, C++, Pearl, anything. That way, understanding logic from a programming perspective is helpful, and hence one can easily grab the data science stuff.
  • Probability & Statistics: With a basic understanding of probability & statistics, this data scientist training course can be taken smoothly. This is because data science deals with many statistical tests and inferences, knowing probability and statistics will be a great boost.

Target Audience

  • Students of Analytics: If you’re a student of data science/analytics and want your career to drift deeper into that, this data scientist training is a sure-shot solution for it. This data scientist course will help you bridge the gap between your college curriculum and industry related to Data science by giving you practical and live experiences of projects, which deal with data manipulation, data massaging, data visualization, storytelling.
  • Statisticians & Model Developers: Data science deals with model generation and machine learning. If you want to fine-tune your knowledge of statistics and model generation, go ahead with this course. This data scientist training course will showcase lots of model generation use cases.
  • Professionals: If you are among auditors, solution recommenders, project managers, or in a client-facing role, etc., the Data Scientist course will be an addon and help you excel more in your career. That’s because you will be able to analyze and measure every bit of your task with analytics and data science. You can impress customers with data visualization and various facts extracted from their data.

Course Ratings

  • Daniel L Boyd
    Great Intro Course

    This was an excellent introduction course to Pig. Excellent comparisons. The instructor was clear, to the point, and provided easy to follow walk throughs throughout the entire course.

    Daniel L Boyd

  • Maurizio Oggiano
    Nice course

    The course is clear and with a lot of examples.

    Maurizio Oggiano

  • Anuj Vohra
    Great trainers

    eduCBA is an ultimate online learning tool as it is simple to use and manage. The training materials are quite excellent and very helpful.

    Anuj Vohra

  • JIYEON CHOI
    Data Science with Python

    I found this course very helpful. The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills

    JIYEON CHOI

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