Best Machine Learning Course in Bhivandi - Online Training Classes Available

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  • Learn Machine Learning course in Bhivandi with Guaranteed Job Placement! Get certified from the best Machine Learning training institute in short duration and reasonable fees. Online classes available. more info

  • About Our Data Science Certification Course -

    Learn from basics of Python to advanced A.I. and Analytics modules with projects under or Experts. Can be learnt by both freshers and experienced to become a Data Science Professional

  • Jobs Roles Targeted -

    Data Scientist, Machine Learning Engineer, Data Analyst etc.

  • Any Pre-requisites -

    None. Any one from IT or non IT can learn. Individual courses / customized training available.

Syllabus

Syllabus

Data Science & Analalytics Course
  • Introduction & Installation
    • Introdution to Python & Python Analytics or Adv. Python
    • Python / Anaconda Installations & Configuration
  • Programming Basics
    • Variables
    • Data Types
    • User Inputs
    • Unpacking
    • Boolean Practice
    • What If, Else and If, Making Decisions
    • Loops
  • Functions
    • Creating Functions
    • Using Built in Functions
  • OOPs Programming
    • Modules
    • Classes & Objects
    • Inheritance
    • Overloading
    • Composition
  • Data Structures
    • List
    • Tuple
    • Set
  • Exception Handling
  • MySQL Server Setup
    • Installing and Configuring MySQL Server
    • Creating Database
    • CRUD Operations
    • Create Tables
      • Insert
      • Update
      • Delete
  • Database Integration with Python
    • Connection to Database from Python
    • Writing functions to handle database operations
    • CRUD Operations in python
  • Web Scrapping
    • Getting Data from Any Website using Python (new)
  • Data Analytics in Python
    • Installing & Understanding Analytics Packages
    • NumPy Array Operations
    • Pandas Data Frame Operations
    • Data Acquisition (Import & Export)
    • Indexing
    • Selection
    • Sorting
    • Filtering
    • Group By
    • Binning
    • Concatenation
    • Merge
    • Append
    • Drop
  • Data Visualization in Python
    • Installing Librarires
      • Matplotlib
      • Seaborn
    • Charts & Plots
      • Histogram
      • Scatter Plots
      • Box Plots
      • Line Chart
      • Bar Chart
      • Pie Chart etc.
    • Dashboards
    • Project
  • Beautiful SOAP library
  • Project
  • Machine Learning Examples
    • Introduction to Machine Learning & Data Analysis
    • Machine Learning Examples
  • Statistics & Exploratory Data Analysis (EDA)
    • Descriptive Statistics
    • Descriptive Analytics
    • Measure of Central Tendency
    • Dispersion
    • Probability Distribution
    • Correlation & Covariance
    • Inferential Statistics
    • Diagnostic Analytics
    • Outliers | Missing Values
    • Sparsity
    • Inferential Statistics
    • Random Sampling
    • Hypothesis Testing
       
  • Supervised Learning
    • Installing & Using Scikit-Learn Package
    • Linear Regression
    • Multi-Linear Regression
    • Decision Tree (CART)
    • Ensemble Learning
    • Random Forest
    • xgBoost
    • K Nearest Neighbors (KNN)
    • Support Vector Machine (SVM)
    • Kernel Functions
    • Naive Bayes Classifier (NBC) / MultinomialNB Algorithm
    • GRID SEARCH CV AND RANDOM SEARCG CV
    • Linear Discriminant Analysis (LDA)
       
  • Unsupervised Learning
    • Hierachical Clustering
    • K Means Clustering
       
  • Dimensionality Reduction
    • Principal Component Analysis (PCA)
       
  • Time Series Forecasting
    • Time Series Data
    • Trend Chart
    • Stationarity
    • Seasonality
    • Moving Average
    • Exponential Smoothing
    • ARIMA
    • GARCH
       
  • Model Improvement & Validation
    • Regularization
    • Lasso
    • Ridge
    • ElasticNet
    • Cross Validation
       
  • Methods
    • Sigmoid Function
    • Entropy
    • Information Gain
    • Gini Index
    • Feature Selection
    • Ensemble Modeling (Bagging | Boosting | Stacking)
    • K Selection / Distance Metrics
    • Kernel Functions
    • Elbow Method
       
  • Metrics
    • MAE / MSE/ RMSE / R2 and Adjusted R2
    • AUC ROC CURVE
    • Precision
    • Recall
    • F1 score
    • Confusion Metrics
  • Only Theory
    • SMOTE and near miss
    • EXTRA TREE CLASSIFIER (Random forest)
    • TPOT
    • LOG LOSS
    • CROSS VALIDATION
    • KERNAL PCA
    • LIGHT GBM and cat boosting
    • DBSCAN
    • MINI BATCH K MEANS
    • Passive Aggressive Classifier Algorithm
    • Facebook Prophet
    • time series RNN LSTM
       
  • When to Use Which Algorithms!
     
  • Projects / Case Studies
    • 1) Real Estate Price Prediction
    • 2) Fraud Detection Problem in BFSI domain
    • 3) Disease Detection in Healthcare domain
    • 4) Market Segmentation in Advertising Sector
    • 5) Market Basket Analysis in Departmental Sector
    • 6) Passenger Forecasting in Aviation Sector
    • 7) News Classification in Media Sector
    • 8) Dashboard (Visualization Tool)
    • Please Note - Case studies / projects changes from time to time and will be covered along with their respective modules.
       
  • Intro to AI & Neural Networks
    • Deep Learning vs Machine Learning
    • Tech Advancement
    • All about Artificial Neural Networks (ANN)
    • Understand How Deep Neural Network Works?
    • Different variants of Gradient Descent
    • Stochastic Gradient Descent vs Adam vs Others
    • Hyper parameter Tuning
    • Batch Size
    • Learning Rate
    • Momentum
       
  • Deep Learning in Python
    • Deep Learning packages in python
    • Google TensorFlow Framework
    • Model Building with default TFLearn API
    • Keras Vs TFLearn Vs Pycharm APIs
    • Model Building with Keras API Wrapper
    • Activations
    • Optimizers
    • Losses
    • Validation
    • Evaluation Metrics
    • Keras Backend
    • Callbacks - Early Stopping, TensorBoard
       
  • CNN - Convolutional Neural Networks
    • Understanding Architecture & Visualizing a CNN
    • Stochastic Gradient Descent vs Adam vs Others
    • Hyper parameter Tuning
    • Batch Size
    • Learning Rate
    • Momentum
       
  • Transfer Learning
    • vgg16
      • Activations
      • Optimizers
      • Losses
      • Validation
      • Evaluation Metrics
      • Keras Backend
      • Callbacks - Early Stopping, TensorBoard
    • vgg19
      • Kernel
      • Depth
      • Pooling
    • resnrt 50
       
  • NLTK
    • Simple NLTK
      • Stemming
      • Lemitaization
      • Regex
      • Stopwords
      • Corpus
      • Unigram
      • Bigram
      • Trigram
    • BAG fo words(count vectorization)
    • TD-IDF-term frequency inverse document frequency 1
    • Word embedding
      • word 2 vec --cbow / skipgram
      • glove
    • Fasttext
    • Keyed vector
    • LSTM / RNN (bidirentional)
    • GRU(theory - Arthiecture build )
       
  • Projects & Case Studies
    • Image Recognition using MNIST Dataset
    • Object Recognition using CIFAR-10 Dataset
    • Speech Recognition (Google Voice | Alexa | Siri)
    • Sentiment Analysis and Word Clouds
    • Chat Bot Building
    • Please Note - Case studies / projects changes from time to time and will be covered along with their respective modules.
       
  • Oracle 18/21c Installation
  • Basics
    • Oracle Basics
    • Database models
    • ER Model Overview
    • Data types
    • Understanding Test Database
    • Basics Queries
    • Arithmetic and String functions
    • DML Operations - Insert, Update and Delete
    • FETCH command - Top N, Top % Rows
  • Writing Queries
  • Filters
    • DISTINCT
    • BETWEEN
    • IN
    • LIKE
    • NOT
    • NULL
    • AND, OR, NOT etc
    • Using Complex Data Filtering Techniques
  • Sorting
    • Ascending Order
    • Descending Order
    • Complex Sorting
  • Functions
    • String Functions - lower case, uppercase, substring, instring, trim etc.
    • Number Functions
    • Date Manipulation
    • Null Value Functions - NVL, NVL2, NULLIF, COALESCE
    • Conditional Expressions - Case and Decode
  • Groups
    • Basics
    • Grouping functions - AVG, MIN, MAX, COUNT, DISTINCT COUNT etc
    • Grouping Filters - HAVING
    • Rollups & Cubes
  • Analytic (Window) Functions
    • Over() with summary functions
    • Partition By Queries
    • ROW_NUMBER()
    • RANK()
    • DENSE_RANK()
  • Joins
    • Cartesian Product
    • Equi and Non-Equi Joins
    • Left Outer Join
    • Right Outer Join
    • Full Outer Join
    • Self Join
    • Complex Queries - Joins & Groups Integration
  • SET Operators
    • Union
    • Union All
    • Intersect
    • Minus
  • Subquery
    • Single Valued Row Sub Query
    • Multi Valued Sub Query
  • Views
  • Inline Views
  • ROWID & ROWNUM
  • TOP N Analysis or Complex Inline View
  • DDL
    • Tables - Create, Alter, Drop
    • Indexes - Types, Create, Drop
    • Constraints - Not Null, Primary Key, Unique Key, Foreign Key
    • Sequence
    • Synonyms
  • Foreign Keys
  • DML operations - Insert, Update & Delete
    • Insert, Update, Delete & Truncate
    • Common Operations
    • Creating Tables using queries
    • Bulk Data Inserts using Queries
  • Transactions ( T SQL)
    • Commit
    • Rollback
    • Savepoint
  • DCL - Grant & Revoke
  • Project
  • Introduction to Power BI
    • What is Power BI and Why Power BI
    • Installing Power BI Desktop
    • Exploring the Power BI Workflow
    • Adjusting the settings of the Power BI Desktop
    • Comparison of Power BI vs Other Reporting Tools
  • Getting and Transforming Data with Power BI Desktop
    • Connecting to different sources
    • Connecting to multiple sources
    • Different connecting Options(DirectQuery vs Import Data Vs Live Connection)
    • Shaping and transforming data with Power Query
    • Editing,Merging,Appending queries etc
  • Advance Importing techniques without coding
  • Data cleaning & Advance data cleaning
  • Modeling with Power BI
    • Introduction to Modeling
    • Building Relational Models(Setup and Manage Relationships)
    • Creating table relationships
    • Understanding the filter flow
    • Cardinality and Cross filtering
  • DAX
    • Understanding Dax Syntax
    • Calculated Columns vs Measures
    • Common Dax functions and formulae
    • Understanding the evaluation context in DAX
  • Visualising Data with Reports
    • Creating Visualisations
    • Color & Conditional Formatting
    • Setting Sort Order
    • Scatter & Bubble Charts & Play Axis
    • Tooltips
    • Slicers, Timeline Slicers & Sync Slicers
    • Cross Filtering and Highlighting
    • Visual, Page and Report Level Filters
    • Drill Down/Up
    • Hierarchies
    • Constant Lines
    • Tables, Matrices & Table Conditional Formatting
    • KPI's, Cards & Gauges
    • Map Visualisations
    • Custom Visuals
    • Managing and Arranging
    • Drillthrough
    • Custom Report Themes
    • Grouping and Binning
    • Bookmarks & Buttons
  • Introduction to Power BI Service
    • Introduction to the Power BI Service
    • Quick Tour of Power BI Service
    • Connecting to Data from Power BI service
    • Building Blocks of Power BI Service
  • Sharing and Collaboration Tools in Power BI Service
    • Sharing and Collaboration Options Overview
    • Publish from Power BI Desktop
    • Publish Reports to Web
    • Printing and Exporting from Power BI Service
    • Sharing Reports & Dashboards
    • Workspaces (My Workspace vs App Workspace)
    • Publishing Apps in Power BI Service
    • Row Level Security in Power BI Desktop and Service
  • Power BI Gateway and Refreshing Datasets
    • Understanding Gateways in Power BI
    • Difference between Personal and On-Premise Gateway
    • Installation of Personal Gateway
    • Installation of On Premise Enterprise Gateway
    • Setting Up a Gateway in Power BI Service
    • Understanding Data Refresh(Manual vs Scheduled Refresh)
    • Troubleshooting Refreshing scenarios
  • A.I. in Power BI
  • Advance Report techniques
  • Best Practices
  • Pkg1 - Data Science - 3.5 to 4 months
  • Pkg2 - Data Science and Analytics - 6 months
  • Customized training / individual courses available
  • Upcoming Batches
  • Live Online:
  • Data Science & A.I. - 3.5 to 4 months - ₹30000 - ₹25000 (Limited Period)
  • Data Science, A.I. & Analytics - 6 months - ₹43000 - ₹38000 (Limited Period)
  • Classroom (Thane) - Get Fees
  • Fees inclusive of GST
  • Upcoming Batches
Data Science Course | Data Science Career Path

Tools You Will Learn

Data Science Projects

Few of the projects covered in one of our batches

Why get Trained from us ?

10 yrs in IT Training
ISO Certified Institute
Trained Globally
Training from Experts
100% Job Oriented Courses
Reasonable Fees
100% Practical Training
Interview Preparation
Study Material / Notes
Live Projects / Case Studies
1000+ Companies
Lots of Career Opportunities etc.
Lots of students got placed in ongoing training or in just 2 months of course completion! Thousands trained.
You can be the Next Placed Student,

Contact Us


Mon to Sat - 10am to 7pm & upto 4 pm on Sun

Call us -
+91-7506252588
+91-7276681665

Email us -
info@qxpsols.com

101, 1st Floor, Prestige Chambers CHS Ltd., Behind Dr. Babasaheb Ambedkar Statue, Besides Maurya Hotel, opp. Platform 2 Thane west rly stn.

Inquiry Form


FAQs

Overall 1000+ Companies - Few Mentioned Below:

  • 1. Darwin Platform Group of Companies
  • 2. Expound Technivo Pvt Ltd
  • 3. Aniruddha Telemetry Systems
  • 4. Acura Solutions
  • 5. Yash Technologies
  • 6. AQM Technologies Pvt Ltd
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  • ... 1000+ companies

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