Data Science, Analytics & Machine Learning Course

(5 customer reviews)

Description
Reviews (5)

PROGRAM DESCRIPTION AND CONTENT

Build your Career in Next-generation Tech of Data Science start your exciting career into the world of data right now. This course intent is to train you to become a job-qualified data scientist, analyst, or a data engineer. at ERP College life and interactive data science and machine learning classes, you will be introduced to real-life scenarios and with easy to follow python examples, moreover, you will understand the leading problems of businesses and design strategies that will produce significant impacts and deeper understanding of any business, healthcare or scientific problem.

in this data science, course students will be taught the basic foundations followed by the advanced techniques of Data Science and machine learning. This being said, students are not required to have any previous knowledge about any of the technology, tools, and applications provided in this course.

ERP Colleges Data Science program aims toward teaching students to master skills in the following:

  • Basic Programing Skills in Pyton and R
  • Data Visualization using GGplot and Matplotlib
  • Decision Trees
  • Linear and Logistic Regression
  • Statistics
  • Regression Models
  • Data Mining
  • Web Scraping and Data Wrangling
  • SQL
  • Hadoop
  • HIVE

You will also be introduced and trained to perform the following case studies

  • Business Hypothesis Testing to Find Employment Status versus Propensity for Term Deposits
  • Model Iteration 2 – Logistic Regression Model with Feature Engineered Variables
  • Train a Random Forest Classifier on the ISOLET Dataset
  • Perform Customer Segmentation Analysis in a Bank Using k-means
  • Find an Optimal Model for Predicting the Critical Temperatures of Superconductors
  • Mushroom Poisoning analysis
  • Train and Analyze a Network Intrusion Detection Model
  • Analyzing Churn Data Using Visual Data Analysis Techniques
  • Feature Engineering on a Financial Dataset
  • Finding the Best Balancing Technique by Fitting a Classifier on the Telecom Churn Dataset
  • Comparison of Dimensionality Reduction Techniques on the Enhanced Ads Dataset
  • Fitting a Logistic Regression Model on Credit Card Data
  • Building a Classification Model with Features that have been Generated Using Featuretools
  • Train and Deploy an Income Predictor Model Using Flask

Earning this data science certificate requires intensive training on different data sets, with the help of instructor-led classes, small class sizes, and applied-learning you will gain the experience needed to be in the job market immediately

DATA SCIENCE CAREER PERSPECTIVE:

Certified Data Scientists are one of the highest paid professions in any analytic organization and are ranked in the top 5 best jobs of 2019 (source: Indeed). According to Indeed, the average base salary for a Data Scientist is $83,000 a year and this can go as high as $110,000 a year, when in a Senior Data Scientist position. Certified Data Scientists are the highest in business demand, earning more than the average IT employees.

The top respondent for the job title SAP Consultant is from International Business Machines (IBM) corp., where the average pay is $90,175 a year. Other leading companies such as CGI Group Inc., reports salaries as high as $83,884 and on the lower spectrum, Tata Consultancy Services Limited pays an average of $63,500 (source: PayScale).

Consider using the following statistics when trying to justify the need for a big data initiative:

SAP S/4HANA has seen nearly 30 per cent growth of the customer base in 2019. The program is being utilized in enterprises in an array of industries from retail, manufacturing, utilities, and energy. (source: Bloomberg, Global Demand Grows for SAP’s S4/HANA ERP Software, August 2019)

Bad data costs US businesses, $600 billion alone annually; by 2025, the Data Science analytics sector in India is estimated to grow eightfold, reaching $16 billion (source: Fathom, Lead like a Marketer, Think like a CEO).

DATA SCIENCE CAREER PATH

MACHINE LEARNING ENGINEER

Machine Learning Engineers are required to build machine learning systems as well as implement and maintain machine learning market applications in technology and business products. Using Keras library in tensorflow, the key focus of the system is scale-ability. This career path requires expert-level programming skills in ‘R’ or Python and comprehensive knowledge in machine learning models and their applications according to the business sector needs.

DATA ENGINEER

Data Engineers design, build and maintain data structures for large-scale technology applications, as well as supervise and manage an entire data life cycle. This career path requires strong software engineering and learning skills.

DATA SCIENTIST

Data Scientists perform advanced technical analysis to understand complex systems and make related forecasts about them. This is done by using scientific and mathematical methods such as statistics, mathematics and computer science with the main mission of extracting useful patterns and insights from data. The results are demonstrated using statistical models, visualizations and product data.

DATA ANALYST

Data Analysts are expected to use and implement tools such as Excel, SQL, ‘R’ or Python and conclude data to answer specific questions. Data Analysts must have a deep understanding of the organizations’ data. This career path requires some visualization of data to guide the organization to make valuable judgments by taking and implementing key business decisions.

PROGRAM OUTCOME

Our Data Science Program certificate focuses on job orientation technical skills, and the technical knowledge necessary to consolidate, cleanse, and standardize enterprise data into SAP-HANA data warehouse systems. As a data science student you will gain the skills needed to store, manage, process & analyze large data sets, design advanced data systems, structures & algorithms and develop machine learning models to discover new Insights and hoard big data using SAP-HANA system. Moreover, with our data science program, you will boost your career potential and put you on the right path to become a certified data science expert. for those who are already professionals in data science and would like to refresh their knowledge or get advanced in their careers, please check our our Data Science Boot Camp.

5 reviews for Data Science, Analytics & Machine Learning Course

  1. Fanni

    Super infoamrtive writing; keep it up.

  2. Zak Kalanski

    it was very hard in the beggning but then as we went through the course, everything start making sense i really enjoyed the course, small classes on the 14th floor of downtown calgary, the great thing about the course is that its not just data science but its that with sap hana, the highest paid data scientest in the industry, the only thing is that sometimes there is high noises comming out of the lunch room

  3. Ayodele John

    Very dynamic outline and very relevant to my supply chain analyst position.The instructor approached the course in full detail and projects more resources to enable us sharpen our analytic skills. i would definitely recommend this course to everyone and anyone looking at the next big Discovery.

  4. Ivan K

    The professor, Edward, is great at teaching the course. He expertly teaches all the materials, coding and applications that you will need on the job. The only issue is that the course is currently only 3 months, although the professor is able to squeeze all the materials within that time frame, it is difficult to digest and practice the content he has provided, especially if you have a full-time job. I hope that in the future, ERP College will extend the course from 3 months to 4 months, so that there is more time of the students to practice in class.

  5. Henry Nwachukwu

    My appreciation to ERP for developing this course and using a good hand to teach the course. The machine learning aspect entail lots of demonstration with Machine learning algorithms helping students not to only be good at Exploring data but to derive quick insight from the EDA and so can easily know the best algorithm needed for your machine learning.
    This program is full packed and well structured. I would only recommend future aspiring students to look into basic statistics as the knowledge is highly needed when your are doing Exploratory Data Analysis (Uni-variant, or multivariate) . Understanding relationship is very essential for effective and accurate model development.

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