Artificial Intelligence Certification

1. Artificial Intelligence Certification Certified By Microsoft.

2. Let’s Learn! Technology doesn’t innovate. People do.That is the reason we put individuals first, so we can engage them to arrive at their maximum capacity with innovation. The fast pace of innovation and business today requests a learning approach that fits the necessities of both the individual and the organization. We built a learning system to reflect that need. Adapting today requires a guided methodology through the intricate number of formal and casual learning alternatives. It requires a methodology that envelops the top learning techniques utilized today and adjusts them to help hierarchical results. Our learning ecosystem is designed to support how learning is done today and evolves to meet advances in technology and individual learning needs. Integrating the world’s largest collection of proprietary and IT partner content, resources, and expertise with a global instructor pool of more than 300 real-world experts, Vepsun Technologies delivers custom learning to global organizations no matter where their workforce is located to drive quantifiable results.. 2A Great Place For Education | Vepsun.in

3. Executive Program in Artificial Intelligence Technology Certified by Microsoft. 3A Great Place For Education | Vepsun.in

4. 01 Learning Path Introduction to Python  Concepts of Python Programming Data Science Fundamentals  Introduction to Data Science  Configuration of Development Environment  Real World Use-Cases of Data Science  Variable and Strings  Walkthrough of Data Types  Functions, Control Flow and Loops  Data Science Project Lifecycle  Tuple, Lists and Dictionaries  Standard Libraries Introduction to NumPy  Basics of NumPy Arrays  Mathematical Operations in NumPy  NumPy Array Manipulation  NumPy Array Broadcasting 02 Learning Path Data Manipulation with Pandas  Data Structures in Pandas-Series and Data Exploratory Data Analysis  Introduction to Exploratory Data Analysis Frames (EDA) Steps  Data Cleaning in Pandas  Plots to Explore Relationship Between Two  Data Manipulation in Pandas Variables  Handling Missing Values in Datasets  Histograms, Box plots to Explore a Single  Hands-on: Implement NumPy Arrays and Variable Pandas Data Frames  Heat Maps, Pair plots to Explore Correlations Data Visualization in Python  Plotting Basic Charts in Python  Data Visualization with Matplotlib  Statistical Data Visualization with Seaborn  Hands-on: Coding Sessions Using Matplotlib, Seaborn Package 4A Great Place For Education | Vepsun.in

5. 03 Learning Path Introduction to Machine Learning Linear Regression  What is Machine Learning?  Introduction to Linear Regression  Use Cases of Machine Learning  Use Cases of Linear Regression  Types of Machine Learning - Supervised to  How to Fit a Linear Regression Model?  Evaluating and Interpreting Results from Unsupervised methods  Machine Learning Workflow Linear Regression Models  Predict Bike Sharing Demand Logistic Regression  Introduction to Logistic Regression  Logistic Regression Use Cases  Understand Use of odds & Logic Function to Perform Logistic Regression  Predicting Credit card Default Cases 04 Learning Path Decision Trees & Random Forest Model Evaluation Techniques  Introduction to Decision Trees & Random  Introduction to Evaluation Metrics and Model Forest Selection in Machine Learning  Understanding Criterion (Entropy &  Importance of Confusion Matrix for Information Gain) used in Decision Trees Predictions  Using Ensemble Methods in Decision Trees  Measures of Model Evaluation - Sensitivity,  Applications of Random Forest Specificity, Precision, Recall & f-score  Use AUC-ROC Curve to Decide Best Model Dimensionality Reduction using PCA  Introduction to Curse of Dimensionality  What is Dimensionality Reduction?  Technique Used in PCA to Reduce Dimensions  Applications of Principle Component Analysis (PCA)  Optimize Model Performance using PCA on SPECTF heartdata 5A Great Place For Education | Vepsun.in

6. 05 Learning Path Naive Bayes Classifier K-NearestNeighbours  Introduction to Naïve Bayes Classification  Refresher on Probability Theory  Applications of Naive Bayes Algorithm in Machine Learning  Classify Spam Emails Based on Probability  Introduction to K-NN  Calculate Neighbours using Distance Measures  Find Optimal Value of K in K-NN Method  Advantage & Disadvantages of K-NN Support Vector Machines K-Means Clustering  Introduction to SVM  Figure Decision Boundaries Using Support Vectors  Identify Hyperplane in SVM  Applications of SVM in Machine Learning  Introduction to K-Means Clustering  Decide Clusters by Adjusting Centroids  Understand Applications of Clustering in Machine Learning  Segment Hands in Pokerdata 06 Learning Path Time Series Forecasting Apriori Algorithm  Components of Time Series Data  Interpreting Autocorrelation & Partial Autocorrelation Functions  Introduction to Time Series Analysis  Stationary Vs Non Stationary Data  Stationary data and Implement ARIMA model  Applications of Apriori algorithm  Understand Association rule  Developing product Recommendations using Association Rules  Analyse Online Retail Data using Association Rules Recommendation Systems  Introduction to Recommender Systems  Types of Recommender Systems - Collaborative, Content Based & Hybrid  Types of Similarity Matrix (Cosine, Jaccard, Pearson Correlation)  Segment Hands in Poker DataBuild Recommender systems on Movie data using K-NN Basics 6A Great Place For Education | Vepsun.in

7. 07 Learning Path Linear Discriminant Analysis Anomaly Detection  Recap of Dimensionality Reduction Concepts  Types of Dimensionality Reduction  Dimensionality Reduction Using LDA  Apply LDA to Determine Wine Quality  Introduction to Anomaly Detection  How Anomaly Detection Works?  Types of Anomaly Detection: Density Based, Clustering etc. NET Based Commands  Detect Anomalies on Electrocardiogram Data Ensemble Learning  Introduction to Ensemble Learning  What are Bagging and Boosting techniques?  What is Bias Variance Trade Off?  Predict Wage (annual income) Classes from Adult Census Data 7A Great Place For Education | Vepsun.in

8. Artificial Intelligence INR. 39,990* * Inclusive of all Taxes Enroll Now COMPANY INFORMATION Vepsun Technologies Pvt . Ldt. 1st Floor, 104, S R Arcade, 6th Mail: - info@vepsun.com Contact No. : 090 36363 007 / 090 35353 007 Website: https://vepsun.in/ 8A Great Place For Education | Vepsun.in Cross, Marathahalli, Bangalore - 560037.