Data Science Training in Des Moines

Ideal Data Science Training in Des Moines

The most excellent Data Science Training is offered by SynergisticIT, which will provide you with the most in-demand skills to start a career as a Data Scientist. People who want to understand how to use data-driven solutions in the real world should attend this fast-paced training. It progresses you from the principles of data science to more complex ideas. Through numerous hands-on activities, including case studies, capstone projects, and practical assignments, candidates in our task-based training are given the opportunity to further their topic competence. After completing our ideal Data Science Training in Des Moines, you'll be capable of creating predictive models, automating processes, using Python to clean data, modifying databases, and conducting data analysis.

Why learning Data Science in Des Moines is fruitful?

Here are the top reasons are given below to pursue a career in Data Science:

  • The need for Data Science specialists is growing. By 2026, the number of Data Science employment is expected to grow by 28%, according to the U.S. Bureau of Labor Statistics. In the U.S., it will result from 11.8 million other engagements in data science. You will thus have many job prospects if you pursue Data Science training in Des Moines.

  • Learning Data Science can help you break through in your job. According to reports, Data Scientists are the highest-paid computer professionals, with typical annual salaries ranging from $104,000 to $155,000 depending on experience, region, and domain.

Why learning Data Science in Des Moines is fruitful
  • Data Scientist, Big Data Engineer, Data Visualization Developer, Database Administrator, Analytics Manager, Statistician, BI Engineer, etc., are just a few of the professional paths available in data science. As a result, if you develop the essential Data Science skills, you will have a variety of job options.

  • Data Scientists are in short supply compared to the growing demand for them. According to a recent poll, a shortage of knowledgeable data scientists is available for employment. Utilize this chance to improve your skills through Data Science Training in Des Moines and match the market's needs.

  • Data science is used in some way by every primary sector, including healthcare, finance, manufacturing, retail, information technology, and education. Learning data science can therefore expand your job options as well as provide you access to positions in a variety of industries.

Insight into the course curriculum of our Data Science Training

Our job-oriented curriculum at SynergisticIT is built around the most recent technological developments in the area of data science. Through this method, you can learn multidisciplinary skills like machine learning,  decision trees, predictive modeling, data visualization, data analysis, AI, data structures, data manipulation, Python, etc. You will receive 24/7 support from our live professors during this online Data Science training in Des Moines. By doing this, we can guarantee that you will breeze through our demanding training.

Introduction to Data Science with Python

  • What is Data Science & Analytics?
  • Common Terms in Analytics
  • What is Data & its Classification?
  • Relevance in industry and need of the hour
  • Types of problems and business objectives in various industries
  • Critical success drivers
  • Overview of analytics tools & their popularity
  • Analytics Methodology & problem-solving framework
  • List of steps in Analytics projects
  • Build Resource plan for analytics project
  • Finding the most appropriate solution design for the given problem statement
  • Project plan for Analytics project & key milestones based on effort estimates
  • How leading companies are harnessing the power of analytics?
  • Why Python for data science?

Python Introduction & Data Structures

  • Python Tools & Technologies
  • Benefits of Python
  • Important packages (Pandas, NumPy, SciPy, Scikit-learn, Seaborn, Matplotlib)
  • Why Anaconda?
  • Installation of Anaconda & other Python IDE
  • Python Objects, Numbers & Booleans, Strings, Container Objects, Mutability of Objects
  • Jupyter Notebook
  • Data Structures
  • Python Practical Session / Task

Numerical Python (NumPy)

  • Data Science and Python
  • What is NumPy?
  • NumPy Operations
  • Types of Arrays
  • Basic Operations
  • Indexing & Slicing
  • Shape Manipulation
  • Broadcasting
  • NumPy Practical Session / Task

Pandas Data Analysis

  • Why Pandas?
  • Pandas Features
  • Pandas File Read & Write Support
  • Data Structures
  • Understanding Series
  • Data Frame
  • Pandas Practical Session / Task Data Standardization
  • Missing Values
  • Data Operations
  • NumPy Practical Session / Task

Matplotlib & Seaborn Data Visualization

  • What is Data Visualization?
  • Benefits & Factors of Data Visualization
  • Data Visualization Considerations & Libraries
  • Data Visualization using Matplotlib
  • Advantages of Matplotlib
  • Data Visualization using Seaborn
  • What is a Plot and its types?
  • How to Plot with (x,y)?
  • How to Control Line Patterns and Colors
  • How to Implement Multiple Plots?
  • Matplotlib Practical Session / Task

Data Manipulation: Cleansing – Munging

  • Data Manipulation steps (Sorting, filtering, merging, appending, derived variables, etc)
  • Filling the missing values by using Lambda function and Skewness.
  • Cleansing Data with Python

Data Analysis: Visualization Using Python

  • Introduction exploratory data analysis
  • Important Packages for Exploratory Analysis (NumPy Arrays, Matplotlib, seaborn, Pandas, etc)
  • Univariate Analysis (Distribution of data & Graphical Analysis)
  • Bivariate Analysis (Cross Tabs, Distributions & Relationships, Graphical Analysis)
  • Creating Graphs- Bar/pie/line chart/histogram/ boxplot/ scatter/ density etc)
  • Descriptive statistics, Frequency Tables & summarization

Introduction to Artificial Intelligence (AI) & Machine Learning (ML)

  • What is Artificial Intelligence & Machine Learning?
  • What is Big Data?
  • Understanding the difference between Artificial Intelligence, Machine Learning & Deep Learning
  • Artificial Intelligence in Real World-Applications

Machine Learning Techniques & Algorithms

  • Types of Machine Learning
  • Machine Learning Algorithms
  • Hyper parameter optimization
  • Hierarchical Clustering
  • Implementation of Linear Regression
  • Performance Measurement
  • Principal component Analysis
  • How Supervised & Unsurprised Learning Model Works?
  • Machine Learning Project Life Cycle & Implementation
  • What is Scikit Learn, Regression Analysis, Linear Regression?
  • Difference between Regression & Classification
  • What is Logistic Regression and its implementation?
  • Best Machine Learning Approach

Decision Tree and Random Forest Algorithm

  • What is a Decision Tree and how it works?
  • What is Entropy, Information Gain, Decision Node?
  • In-depth study of Random Forest and understanding how it works?

Naive Bayes and KNN Algorithm

  • What is Naïve Bayes?
  • Advantages & Disadvantages of Naïve Bayes
  • why KNN?
  • Practical Implementation of Naïve Bayes
  • What is KNN and how does it work?
  • How do we choose K?
  • Practical Implementation of KNN Algorithm

Support Vector Machine Algorithm

  • What is Support Vector Machine (SVM)?
  • How Does SVM Work?
  • Applications of SVM
  • Why SVM?
  • Practical Implementation of SVM

Model Deployment & Tableau

  • Flask Introduction & Application
  • Django end to end
  • Working with Tableau
  • Data organisation
  • Creation of parameters
  • Advanced visualization
  • Dashboard data presentation

Introduction to Statistics

  • Descriptive Statistics
  • Sample vs Population Statistics
  • Random variables
  • Probability distribution functions
  • Expected value
  • Normal distribution
  • Gaussian distribution
  • Z-score
  • Central limit theorem
  • Spread and Dispersion
  • Hypothesis Testing
  • Z-stats vs T-stats
  • Type 1 & Type 2 error
  • Confidence Interval
  • ANOVA Test
  • Chi Square Test
  • T-test 1-Tail 2-Tail Test
  • Correlation and Co-variance

Introduction to Predictive Modelling

  • The concept of model in analytics and how to use it?
  • Different Phases of Predictive Modelling
  • Popular Modelling algorithms
  • Different kinds of Business problems - Mapping of Techniques
  • Common terminology used in Modelling & Analytics process

Data Exploration for Modelling

  • Visualize the data trends and patterns
  • Identify missing data & outliers’ data
  • EDA framework for exploring the data & identifying problems with the data by the help of pair plot.
  • What is the need for structured exploratory data?

Data Preparation

  • Merging
  • Normalizing the data
  • Feature Engineering
  • What is the need for Data preparation?
  • Aggregation/ Consolidation - Outlier treatment - Flat Liners - Missing Values-Dummy creation - Variable Reduction
  • Variable Reduction Techniques - Factor & PCA Analysis
  • Feature Selection
  • Feature scaling using Standard Scaler
  • Label encoding

Ensemble Learning Techniques

  • In-depth study of Ensemble Learning with Real Examples
  • How to Reduce Model Errors with Ensembles
  • Understanding Bias and Variance
  • Different Types of Ensemble Learning Methods
  • Feature Selection
  • Feature scaling using Standard Scaler
  • Label encoding

Web Scraping using Python Beautiful Soup

  • What is Web Scraping & Why Web Scraping?
  • Web Scraping using Beautiful Soup Practical Session / Task
  • Difference Between Web Scraping Software Vs. Web Browser
  • Web Scraping using Beautiful Soup Practical Session / Task
  • Web Scraping Considerations & Tools
  • Why Beautiful Soup?
  • Common Data & Page Formats on the Web
  • Practical Implementation of Web Scraping
  • Web Scraping Process
  • What is a Parser?
  • Importance of Parsing
  • What are the various Parsers?
  • How to Navigate the Parsers?
  • How to take Output – Printing & Formatting

Time Series Analysis

  • Why Time Series Analysis?
  • What is Time Series?
  • Time Series Components (Seasonality, Trend, Level & Cyclicity) and Decomposition
  • Classification of Techniques like Pattern based or Pattern less
  • Basic to Advance level Techniques (Averages, AR Models, Smoothening, ARIMA, etc)
  • Use Cases of Time Series Analysis
  • When Not to Use Time Series Analysis?
  • Understanding Forecasting Accuracy - MAPE, MAD, MSE, etc
  • Time Series Analysis Case Study - Practical Session / Task

Deep Learning

  • What is deep learning
  • The neuron
  • How do neural networks work?
  • Back propagation
  • ANN in Python
  • What are convolutional neural networks?
  • Installing Tensor Flow & Keras
  • CNN in Python
  • Activation function & Epoch

Natural Language Processing (NLP) & Text Mining

  • What is Natural Language Processing (NLP) & Why NLP?
  • NLP with Python
  • Sentiment analysis
  • Bags of words
  • Stemming
  • Tokenization
  • What is Text Mining?
  • Text Mining & NLP
  • Benefits, Components, Applications of NLP
  • NLP Terminologies & Major Libraries
  • NLP Approach for Text Data
  • What is Sentiment Analysis?
  • Steps for Sentiment Analysis
  • Sentiment Analysis Case Study - Practical Session / Task
  • Practical Implementation of NLP
  • NLP Case Study - Practical Session / Task

Market Basket Analysis

  • What is Market Basket Analysis & how it is used?
  • What is Association Rule Mining?
  • What is Support, Confidence & Lift
  • An Example of Association Rules
  • Market Basket Analysis Case Study - Practical Session / Task

What are the advantages of choosing SynergisticIT?

SynergisticIT is the most recommended for Data Science training in Des Moines.

Our outstanding faculty has over ten years of real-world expertise in data science.

Since our founding in 2010, we have built strong relationships with tech juggernauts like Apple, Google, Cisco, Deloitte, IBM, and others, enabling us to place individuals in such illustrious businesses.

Candidates are not charged extra to repeat a Data Science training in Des Moise helps 10000of prospective students to pick us. We also offer career coaching and help job prospects get ready for technical interviews by having them take practice exams, answer behavioral questions, administer personality tests and other examinations, etc.

What are the advantages of choosing us

You have lifelong access to the most recent study material when you enroll in our Data Science Training in Des Moines.

We also assist you in creating resumes and job portfolios that adhere to industry standards.

Real-world experience working on projects in data science and case studies is provided to our candidates.

Our goal is to upskill a sizable population in the booming Data Science technology. So that everyone can afford our training, we provide financial assistance through such an Income Share Agreement (ISA).

You will graduate from this Data Science Training with a well-respected degree that can help you stay one step ahead of the competition.

Who are eligible to join this Data Science Training in Des Moines

Who are eligible to join this Data Science Training in Des Moines?

Anyone interested in building a career in data science is welcome to enroll in this course. You do not need to have any prior programming language knowledge. As a result, you are allowed to sign up for this Data Science Training in Des Moines as:

  • College Graduate
  • Fresher
  • Software Programmer
  • Statistician, Economist, and Mathematician
  • Professionals with a logistics or analytical background
  • People working on reporting tools, business intelligence, and data warehousing

Start acquiring valuable Data Science and Data Analyst skills by training at the best Data Science Bootcamp. Create a robust work portfolio to demonstrate your abilities in the field with the assistance of experienced mentors. Let’s help you achieve your career goals. SynergisticIT- Home of the Best Data Scientists and Software Programmers in the Bay Area!

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Frequently Asked Questions on Data Science

What Our Candidates Say About Us ?

Google Reviewer

Being an international student in USA and realizing that I was on the verge of completing my CS degree with not enough experience or skills to crack the interviews I was desperate for some kind of breakthrough. I started looking for a tech Bootcamp which could work with my study schedule and yet offer me…

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Minh Ho

Good place for anyone struggling to find a technology job with bigger name clients. I worked with them for some time like a year back or so and after my experience with them I had upgraded my coding skills to the standards of major it organizations. Synergisticit is in my opinion one of the very…

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Menglee G.

Synergistic IT was the best decision I made for my career. During my time here, I worked on multiple projects and learned a lot of high demand skills for the competitive tech industry. They have amazing trainers who have lots of experience. I would recommend it to anyone who wants to become a professional in…

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